Statistics

In random experiments, most analyses are based on interpretation of the difference between the means of experiment and control groups. Therefore, studying the difference between the variances of the experiment and control groups may also be useful in interpreting the analysis results. This study focuses on interval estimation with sample variance estimators based on Winsorized Mean and Trimmed Mean for the difference of the variances of two nonnormal populations. In the simulation study, confidence intervals based on robust estimators for the difference of the variances of two non-normally distributed populations were compared in terms of coverage probabilities and average length widths. According to simulation study, it was determined that the coverage probabilities of confidence intervals based on robust estimators were very close to the nominal confidence level in any case. However, it was seen that the average length widths of confidence intervals obtained with sample variance estimator based on Trimmed Mean were narrower compared to the average length widths of confidence intervals obtained with sample variance estimator based on Winsorized Mean. In addition, it was determined that these results were the same when the Type I error is different. According to these results, it will be appropriate to prefer interval estimations obtained with sample variance estimator based on Trimmed Mean since it provides narrower confidence interval for the difference of the variances of two nonnormal populations.

Many of the test statistics which used to test $H:\theta=\theta_0$ are constructed under a postulated model. However, when the postulated model is not correct, the true significance level $\alpha^{'}$ will be different than the significance level of the postulated model $\alpha$. The significance level $\alpha$ is used in the test statistic whether or not the hypothesis is rejected or not rejected, so determining the true significance level is important in the hypothesis tests. In this paper, when the normality assumption in hypothesis tests is violated, the true significance level for testing hypothesis about the location $\mu$ and scale $\sigma$ parameters under different contaminated distributions is obtained. As a result, the robustness of significance levels  is investigated.

The adjustment of grid steps which guarantees that particles methods yield no numerical diffusion inevitably induces overshooting errors in the solution of the parabolic partial differential equations with space variable coefficients. In this paper we give an evaluation of the overshooting errors of the "global random walk" algorithm (GRW), a computational efficient method used in simulations for transport in environmental problems. The evaluation is performed by comparisons between the GRW solutions and those of the "biased global random walk" algorithm (BGRW), a cellular automaton, which is computationally more expensive but is also free of overshooting errors. The reference problem was the diffusive transport in a random velocity field, a model for the transport of the contaminant solutes in groundwater. The evaluation reveals that, for an optimum choice of the parameters, GRW results for time intervals of practical interest lie in ranges of acceptable precisi...

Background: A new Ultra performance liquid chromatographic analytical method was developed and validated for estimation of Quercetin in bulk powder. The reverse phase chromatographic elution using UPLC was carried out in gradient mode on C-18 column (Phenomenex Luna 5 µm, 150 mm X 4.6 mm) as stationary phase utilizing a mobile phase composed of Acetonitrile: 0.1 % formic acid buffer (50:50 v/v) with a flow rate of 1 ml/min and injection volume of 10µl.  The analysis was performed at temperature of 400C and detection of eluent was carried out using photo diode array at 371 nm. The newly developed Ultra performance liquid chromatography method was validated in terms of linearity and range, system suitability, specificity, precision, sensitivity, robustness, ruggedness and accuracy as per ICH guidelines. Results: The retention time of quercetin was found to be at 3.9 min with total run time of analysis is 7 minutes. The linearity was observed between the concentration ranges from 0.5 t...

Epidemiological and animal research shows that disease aetiology often has to be evaluated with a life course perspective, starting as close to the time of conception as possible and, furthermore, that genetic predisposition, environmental exposures and social context have to be considered simultaneously. 1 Exposures during the prenatal and postnatal periods have implications for children's health and may also have implications for morbidity occurring later in life, including obesity and cardiovascular diseases, asthma and allergy, cancer, delayed neurodevelopment, mental illnesses and more. Birth cohort research has a long history in Europe and extensive collaborations have been established. The Rhea cohort is the only pregnancy cohort established and followed up in Greece and one of the very few cohorts in a large area in southern Europe and the eastern Mediterranean where birth cohort research has just started to emerge, and some of the circumstances observed in the Rhea population actually reflect patterns in this wider region. The research team of Rhea study specializes on specific research areas, including obesity, neurodevelopment and child asthma, but also addresses social, environmental and lifestyle factors specific to the Greek society such as use of pesticides, adherence to the Mediterranean diet or psychosocial factors at a time of economic crisis. The name of the cohort 'RHEA' is inspired by 'P ea' the mythological wife of Kronos (Cronus). The Rhea study was established in 2007 in the island of Crete, aiming to recruit a representative sample of motherchild pairs from early pregnancy and to follow them up to young adulthood. The uniqueness of this cohort is that it takes place in the island of Crete where the beneficial effect

En bovinos productores de leche la curva de lactancia (CL) se ha analizado con modelos no lineales (MNL), y recientemente se ha implementado la metodología de MNL mixtos. Los objetivos fueron: a) ajustar un MNL a la CL a 240 días; b) comparar MNL vs MNL mixtos; c) estimar producción al pico (PMAX) y total a 240 días (PTOTAL), así como días para alcanzar la producción máxima (DPMAX). Se analizaron 15,324 observaciones de producción diaria (kg), correspondientes a primera lactancia de 2,809 vacas Siboney, con fecha de parto de 2000 a 2012 en 28 hatos. Se evaluaron cinco MNL: Wood, Wiltmink, Cobby, Brody y Sikka. Se realizaron dos análisis con el procedimiento NLMIXED de SAS: ANA1, incluyó sólo el efecto aleatorio de los residuales; y ANA2, incluyó el efecto aleatorio correspondiente a un coeficiente de regresión, más los residuales. La selección del modelo con mejor ajuste se realizó con: error de predicción promedio; varianza del error de predicción; estadístico Durbin Watson; coefic...

Background: A crucial question when developing reference intervals is whether different subpopulations need their own reference interval or if a single joint reference interval can be used. It is reasonable to use partitioned reference intervals in situations where a single interval results in considerable variation in sensitivity between subpopulations. The aim of partitioning is to harmonize the sensitivity of the reference intervals, i.e., to make the sensitivity similar for all patients, regardless of patient characteristics. Statistical criteria to identify when partitioning is adequate have been developed over the last two decades. These criteria are applicable when considering two subpopulations, but recently a procedure for considering several subpopulations has been developed. When several subpopulations are considered, there is a possibility that some subpopulations could form a group or cluster that could share a common reference interval. However, there is no formal systematic approach to indicate how to divide these subpopulations into clusters. The aim of this study was to suggest such a systematic approach for clustering. Methods: A clustering technique was applied to data including several subpopulations. The technique is based on measuring the distance between separated reference limits and successively pooling subpopulations divided by short distances. A cluster is defined by a group of subpopulations that are close to each other and that differ from subpopulations in another cluster. A cluster recruits new subpopulations as long as the subpopulations can be pooled without violating a partitioning criterion. Conclusions: We have suggested a procedure for partitioning a number of Gaussian (or Gaussian-transformable) subpopulations into clusters. This is the only formalized procedure indicating how to analyze several subpopulations and identify a suitable number of groups and reference intervals. Using a computer program developed for partitioning issues, the approach was easy to adopt.

This study looks into how using ChatGPT in statistics classes affects students' participation and motivation in UAE higher education. A difficult subject that is frequently seen negatively, statistics can lower students' motivation and involvement. This study investigates how such integration might enhance students' learning experiences by utilizing ChatGPT, an AI-driven platform that offers interactive and tailored help. Regression analysis was used in a quantitative study design to evaluate the connection between ChatGPT integration and shifts in student involvement and motivation. University students were given a structured survey to complete in order to get data on their motivation and level of involvement after utilizing ChatGPT for their statistics assignment. The findings show that ChatGPT has a statistically significant beneficial impact on motivation and engagement, indicating that AI-based tools can be crucial in fostering a more encouraging and stimulating learning environment. By demonstrating ChatGPT's capacity to satisfy students' demands for independence and individualized instruction, these results advance educational theory in line with Self-Determination Theory. In order to improve learning results and student happiness in higher education, the study's managerial implications for educational institutions suggest using AI tools to boost student motivation and engagement.

The aim of this research work was to detect students' attitudes towards Statistics in the group of participants of the MA program in Educational Management, and, according to the results, to put into practice relevant methodological strategies for the conduction of the teaching-learning process. In order to achieve this goal a methodology framed within action research guidelines was followed. Contributions of , , among others, built the theoretical fundamentals upon which a scale was adopted for the purpose of surveying the student's opinions about their attitudes towards Statistics, as well as for the design and application of an instrument aimed at measuring their elementary knowledge of Statistics. Among the most relevant results, it can be mentioned that 76% of the students expressed a favorable attitude towards statistics and that the methodological strategies implemented allowed the acquisition of skills and abilities for the analysis of data with SPSS.

In Korea, Korea Proven Bulls (KPN) program has been well-developed. Breeding and evaluation of cows are also an essential factor to increase earnings and genetic gain. This study aimed to evaluate the accuracy of cow breeding value by using three methods (pedigree index [PI], pedigree-based best linear unbiased prediction [PBLUP], and genomic-BLUP [GBLUP]). The reference population (n = 16,971) was used to estimate breeding values for 481 females as a test population. The accuracy of GBLUP was 0.63, 0.66, 0.62 and 0.63 for carcass weight (CWT), eye muscle area (EMA), back-fat thickness (BFT), and marbling score (MS), respectively. As for the PBLUP method, accuracy of prediction was 0.43 for CWT, 0.45 for EMA, 0.43 for MS, and 0.44 for BFT. Accuracy of PI method was the lowest (0.28 to 0.29 for carcass traits). The increase by approximate 20% in accuracy of GBLUP method than other methods could be because genomic information may explain Mendelian sampling error that pedigree information cannot detect. Bias can cause reducing accuracy of estimated breeding value (EBV) for selected animals. Regression coefficient between true breeding value (TBV) and GBLUP EBV, PBLUP EBV, and PI EBV were 0.78, 0.625, and 0.35, respectively for CWT. This showed that genomic EBV (GEBV) is less biased than PBLUP and PI EBV in this study. In addition, number of effective chromosome segments (M e ) statistic that indicates the independent loci is one of the important factors affecting the accuracy of BLUP. The correlation between M e and the accuracy of GBLUP is related to the genetic relationship between reference and test population. The correlations between M e and accuracy were -0.74 in CWT, -0.75 in EMA, -0.73 in MS, and -0.75 in BF, which were strongly negative. These results proved that the estimation of genetic ability using genomic data is the most effective, and the smaller the M e , the higher the accuracy of EBV.

This study discusses the Fuzzy Elimination Et Choix Traduisant La Realite (ELECTRE) method that can be applied to make a decision support. This method was chosen because it is one of the methods used to rank and determine the best alternative. This study aims to determine the results of the application of the fuzzy ELECTRE method which produces alternative solutions in determining employee performance appraisal ratings for the Education and Culture Office of Malang City. Some of the problems that often occur in employee performance evaluation at the Department of Education and Culture in the city of Malang are still ineffective and inaccurate because the calculation process is still manual. Based on this, the effort to reduce the problems above is to implement a Fuzzy Multi Attribute Decision Making decision support system with the fuzzy ELECTRE method. This method requires a process of normalizing the decision matrix (X) into a comparable scale, then weighting the normalized matrix...

The most developed forecasting method currently is the time series, which uses a quantitative approach with past data as a reference for future forecasting. Fuzzy time series is a solution that uses time series data by applying fuzzy methods in forecasting. This research using fuzzy time series is applied on data from the sale of the Republic of Indonesia Employee Cooperative (KPRI) Selorejo District, Blitar Regency in 2015-2021. This study describes the problem of forecasting the results of cooperative sales using the Fuzzy Time Series (FTS) which was developed with the High Order. The development of the method is done by improving the FTS method with mathematical rules and is applied to the stages of the process of forecasting the results of cooperative sales. Testing the results of the High Order Fuzzy Time Series forecasting using the best Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE) accuracy values . The High Order Fuzzy Time Ser...

Clean drinking water is an essential component to maintaining public health. Methods used to purify drinking water include the addition of disinfectants, chemical methods of control, such as ozone or ultraviolet radiation, and physical methods of control, such as filtration. Disinfectants and filtration are the most widely used methods to ensure high-quality drinking water. However these methods do not sterilize the water, and there are still concerns as to whether or not some methods are better than others at reducing bacterial loads. This study tested water from traditional drinking fountains, Poland Springs® water cooler dispensers, and from Halsey-Taylor Filtered Single HAC Coolers with Hydroboost® Bottle Fillers. Water samples were collected from each source types on various days, plated onto Nutrient agar, and analyzed to count CFUs/mL for each source. We found that there is no statistical difference in the mean bacterial CFUs/mL among the three water sources tested. We conclu...

The ant colony optimization (ACO) is widely used for combinatorial optimization problems, although it can suffer from fast convergence to local minima. In order to provide a versatile implementation of ACO, we present a parallel multicolony strategy with an improved cooperation scheme for binary combinatorial problems. Our proposal is based on a self-adaptive method, which assigns appropriate run-time cooperation levels to each problem based on its size and available computational resources. We evaluate this proposal with problems with different levels of cooperation and number of processes. All these configurations combined show its flexibility as a versatile solver for this type of problems.

This paper presents novel results for the high order capacity statistics (HOS) of equal gain combining (EGC) diversity receivers. The proposed methodology to obtain these results includes in the analysis the study of generalized fading channels and arbitrary number of receiving antennas. Analytical expressions for the n-th order capacity statistics as well as for the amount of dispersion (AoD), the reliability of the signal throughput, the kurtosis and the skewness of the channel capacity distribution have been derived. The validity of the proposed methodology has been verified by means of Monte Carlo computer simulations. Furthermore, it has been shown that previously published results for the first order capacity statistics are included in the analysis as special cases.

The positive and negative predictive values of a binary diagnostic test are measures of the clinical accuracy of the diagnostic test, which depend on the sensitivity and specificity of the diagnostic test and the disease prevalence, and therefore they are two interdependent parameters. The comparisons of predictive values in paired designs do not consider the dependence between predictive values. A global hypothesis test has been studied in order to simultaneously compare the predictive values of two or more binary diagnostic tests when the binary tests and the gold standard are applied to all of the individuals in a random sample. This global hypothesis test is an asymptotic hypothesis test based on the chi-square distribution. Simulation experiments have been carried out in order to study the type I error and the power of the global hypothesis test when comparing the predictive values of two and three binary diagnostic tests, respectively. From the results of the simulation experiments, a method has been proposed to simultaneously compare the predictive values of two or more binary diagnostic tests. The results have been applied to the diagnosis of coronary disease.

The main result of this effectiveness study is that a reading program with a focus on students' poetry reading processes, based on observational learning via eye movement modeling examples, can improve students' reading comprehension for different text types. In a pretest-posttest design with an experimental group (ten classes) and a control group (five classes), students' self-efficacy regarding their own reading process and their reading comprehension were measured. Over a six-week period, teachers of Dutch and their students worked with the six experimental lessons, instead of the regular reading program: students observed and evaluated contrasting peer reading processes, reflected on differences with their own reading process, and then they practiced aspects of a deep reading process. The program resulted in significant progress in the reading comprehension of "expository texts" (ES = .66), "short stories" (ES = .66), and especially "poetry" (ES = .81). Furthermore, the self-efficacy test results show that students in the experimental condition experienced significantly more learning effect after the intervention period than those in the control group. Moreover, based on the learning reports, evaluation tasks and interviews, it appears that the participants in the innovative program have become aware of their reading and how they improved their performance.

I wish to express my gratitude to Mr. PRINCE Olivier and Mr. Ir. KABASELE DYCKOBA Joseph Richard, for their incomparable commitment to supervise my work and their guidance where they could never refuse to receive me even in times when they were too busy. I gained marvellous knowledge as well research skills. My most consistent supporters have always been my family, Mother NYIRAKAMALI Berancille, Uncle Dr. Father Uwitonze Oscar and my sisters and brother. You made sacrifice which enabled to reach this stage in my studies. Thank you for your support and may this achievement reflect the cost of your sacrifice. As you have often displayed greater confidence in my abilities than I have in myself. I could not have reached this stage in life without your encouragement and support. I wish to thank everybody especially Bureau Social de Developpement de Muhanga, Mr NDAGIWENIMANA Ezechiel and family of SIBOMANA Emmanuel who contributed morally or materially, directly or indirectly to the fulfilment of this research. Infinite and incomparable gratitude goes to my lecturers in Department of Statistics Applied to Economy, Faculty of Applied Fundamental Sciences, who gave me a helpful guidance towards this work. Furthermore, I am grateful to all my colleagues and especially my classmates in department of Statistics Applied to Economy for their moral support during the five years of study at INES-Ruhengeri. And, I owe my appreciation too to all staff of INES Ruhengeri who provided me information during this work.

Stojanović, E, Aksović, N, Stojiljković, N, Stanković, R, Scanlan, AT, and Milanović, Z. Reliability, usefulness, and factorial validity of change-of-direction speed tests in adolescent basketball players. J Strength Cond Res 33(11): 3162–3173, 2019—The purposes of this study were to (1) determine the reliability, usefulness, and factorial validity of change-of-direction speed (CODS) tests in adolescent basketball players and (2) evaluate positional differences in test performances. Elite, adolescent male basketball players (n = 53; 17.3 ± 1.0 years) completed 6 CODS tests: “Lane Arrow Closeout,” “Lane Agility Drill,” “Reactive Shuttle Test,” “Run-Shuffle-Run,” “Compass Drill,” and “Modified 505 Test.” Players completed 3 trials of each test. All tests demonstrated acceptable reliability (intraclass correlation coefficient: 0.50–0.88; coefficient of variation: 5.1–7.9%). The typical error (TE) calculated for each test was above the smallest worthwhile change, rating the usefulness o...

We investigate the validity of the bootstrap method for the elementary random variables X 1 , ... ,Xn. For both fix~d and'incre~sing brder k, as n __, oo the cases where µ = EX 1 f= 0, the nondegenerate case, and where µ = EX 1 = 0, the degenerate case, are considered.

The aim of the study is to compare the scores given to the condition of Charolais cows (the herd of Abauj Charolais Corp., Dichaza, Hungary, spring of 2011) (n=213, live weight: 695.6±73.18 kg, age: 5.9±2.06 years) before the grazing season by two independent conformation judges (person A and B). The scoring system (1-9 points) according to Whitman (1975) was used for evaluating the condition. The average condition scores given by the two judges were different only in the second decimal place ( A: 5.76, B: 5.74 points). The median, modus, minimum and maximum values were equal, but the standard deviation was higher (although not significantly) in case of the B judge ( A: 0.544, B: 0.610). By Pearson χ 2 test it could be proved that the condition scores given by the two persons are statistically not independent (319.24, df: 9, p=0.0001), cause their results are highly similar. The value of Spearman correlation is r=0.76 (p=0.0001), which also indicates the similarity of the scores giv...

In a simple graph G without isolated nodes the following random experiment is carried out: each node chooses one of its neighbors uniformly at random. We say a rendezvous occurs if there are adjacent nodes u and U such that it chooses v and v chooses u; the probability that this happens is denoted by 8(G). asked whether it is true that 3(0) 2 8(Kn) for all n-node graphs G, where Kn is the complete graph on n nodes. We show that this is the case. Moreover, we show that evaluating 3(G) for a given graph G is a #P-complete problem, even if only d-regular graphs are considered, for any (1 Z 5. Note: Parts of the results of this paper were reported at ISAAC 2002.

In a simple graph G without isolated nodes the following random experiment is carried out: each node chooses one of its neighbors uniformly at random. We say a rendezvous occurs if there are adjacent nodes u and U such that it chooses v and v chooses u; the probability that this happens is denoted by 8(G). asked whether it is true that 3(0) 2 8(Kn) for all n-node graphs G, where Kn is the complete graph on n nodes. We show that this is the case. Moreover, we show that evaluating 3(G) for a given graph G is a #P-complete problem, even if only d-regular graphs are considered, for any (1 Z 5. Note: Parts of the results of this paper were reported at ISAAC 2002.

Background: Modifying lifestyle risk factors for dementia is a public health priority. Motivation for change is integral to the modification of health-related risk behaviours. This study investigates the psychometric properties of the previously validated tool entitled 'Motivation to Change Lifestyle and Health Behaviours for Dementia Risk Reduction Scale' (MCLHB-DRR) for use in the UK. Methods: A sample of 3,948 individuals aged 50 and over completed the 27-item MCLHB-DRR online. The psychometric properties of the scale were explored via Exploratory Principal Axis Factoring (PAF) with Oblimin rotation. Confirmatory Factor Analysis (CFA) was used to confirm the factor structure using chi-square (χ2), the goodness-of-fit index (GFI), the comparative fit index (CFI), the root mean square error of approximation (RMSEA) and Root Mean Square Residual (RMR) as fit indices to evaluate the model fit. Internal consistency (Cronbach α) was measured for the final scale version. Results: Exploratory Factor Analysis (EFA) resulted in a parsimonious 10-item, two-factor structure (5 items each, factor loadings > 0.3) that explained 52.83% of total variance. Based on the Pattern Matrix, Factor 1 was labelled "Positive Cues to Action" and Factor 2 was labelled "Negative Cues to Action". After addressing some errors in covariances, CFA showed a good fit where all fit indices were larger than 0.90 (GFI = 0.968, CFI = 0.938) and smaller than 0.08 (RMSEA = 0.072, RMR = 0.041). The standardized coefficients of Factor 1 and Factor 2 ranged from 0.30 to 0.73 and were all statistically significant (p < 0.001). The final scale showed moderate to high reliability scores (Factor 1 α = 0.809; Factor 2 α = 0.701; Overall α = 0.785). Conclusions: The new MOCHAD-10 (Motivation to Change Behaviour for Dementia Risk Reduction Scale) is a short, reliable and robust two-factor, 10-item clinical tool for use in preventative health care and research to evaluate motivation to change lifestyle for dementia risk reduction.

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Aim of our research was to conduct a clinical and laboratory analysis of the impact of COVID-19 on pregnancy and the condition of the fetus. Materials and Methods: At the first stage, we conducted a retrospective examination of 50 pregnant women treated at Ternopil Municipal Hospital No.2 (Ukraine) between November 2020 and January 2022 with the history of COVID-19, confirmed by PCR test, and 25 pregnant COVID-19 negative pregnant women (control group). At the second stage, we performed prospective cohort study and involved 40 pregnant women treated with the history of COVID-19, confirmed by PCR, and 10 pregnant COVID-19 negative women with a physiological course of pregnancy as a control group.Women were divided into the following groups: group I -10 women diagnosed with COVID-19 during the first trimester of pregnancy: group II-15 women diagnosed during the second trimester; group III-15 women diagnosed during the third trimester. Ultrasound examination and cardiotocograms were performed to assess fetus status. Blood samples were collected at delivery. To determine whether COVID-19 could alter placental angiogenesis, vascular endothelial growth factor A (VEGFA), PlGF and interleuin-32-α were assessed. results: We identified that concentration of VEGFA was 95.30±5.65 pg/ml in control group. In women who had COVID-19 in first trimester, this index was 1.3 times higher, in second trimester 1.63 times higher and in third trimester by 2 times compared to control group. PlGF concentration was only 27,4 percent in group I, 16 percent in group II and 30 percent in group III,compared to control group. Concentration of interleuin-32-α was 67.27±5.63 pg/ml in control group and increased to 167 percent in group I, by 2.8 times in group II and by 6.3 times in group III compared to control group. conclusions: COVID-19 has a negative impact on placental angiogenesis, including VEGFA and PlGF. Fetal post-COVID-19 syndrome requires timely diagnosis of disorders and further study. Post-COVID-19 syndrome is an immune-dependent pathology in which the processes of protracted cytokine activation occur in the body of a pregnant woman.

The purpose of the study was to determine the reliability and validity of a method developed on the basis of information technologies to control the strength endurance of the core muscles of students with disabilities. Materials and methods. 38 students with disabilities, aged 18–23, who entered the first year of study at the university, voluntarily participated in the study. The studied sample consisted of students with a simple form of disorder in the musculoskeletal system, who have the ability to move independently and perform motor actions. An information-search approach to data collection was used at the theoretical level, and pedagogical testing and methods of mathematical statistics were used at the empirical level. Results. A method for assessing the strength endurance of the core muscles developed on the basis of information technologies is presented. To implement the method, a network of sensors formed by analog and digital sensors, wireless infrared communication devices...

Dadas las implicaciones de carácter éti-co, social y jurídico que se derivan de la uti-lización de test o ítems sesgados contra al-gún grupo de la población, no es de extrañar la proliferación de investigaciones sobre el funcionamiento diferencial de los ítems (Fi-dalgo, 1996a). Se ...

Preserving the robustness of the procedure has, at the present time, become almost a default requirement for statistical data analysis. Since efficiency at the model and robustness under misspecification of the model are often in conflict, it is important to choose such inference procedures which provide the best compromise between these two concepts. Some minimum Bregman divergence estimators and related tests of hypothesis seem to be able to do well in this respect, with the procedures based on the density power divergence providing the existing standard. In this paper we propose a new family of Bregman divergences which is a superfamily encompassing the density power divergence. This paper describes the inference procedures resulting from this new family of divergences, and makes a strong case for the utility of this divergence family in statistical inference.

In real life, we frequently come across data sets that involve some independent explanatory variable(s) generating a set of ordinal responses. These ordinal responses may correspond to an underlying continuous latent variable, which is linearly related to the covariate(s), and takes a particular (ordinal) label depending on whether this latent variable takes value in some suitable interval specified by a pair of (unknown) cutoffs. The most efficient way of estimating the unknown parameters (i.e., the regression coefficients and the cut-offs) is the method of maximum likelihood (ML). However, contamination in the data set either in the form of misspecification of ordinal responses, or the unboundedness of the covariate(s), might destabilize the likelihood function to a great extent where the ML based methodology might lead to completely unreliable inferences. In this paper, we explore a minimum distance estimation procedure based on the popular density power divergence (DPD) to yield robust parameter estimates for the ordinal response model. This paper highlights how the resulting estimator, namely the minimum DPD estimator (MDPDE), can be used as a practical robust alternative to the classical procedures based on the ML. We rigorously develop several theoretical properties of this estimator, and provide extensive simulations to substantiate the theory developed.

Missing data is an important issue in almost all fields of quantitative research. A nonparametric procedure that has been shown to be useful is the nearest neighbor imputation method. We suggest a weighted nearest neighbor imputation method based on L q -distances. The weighted method is shown to have smaller imputation error than available NN estimates. In addition we consider weighted neighbor imputation methods that use selected distances. The careful selection of distances that carry information on the missing values yields an imputation tool that outperforms competing nearest neighbor methods distinctly. Simulation studies show that the suggested weighted imputation with selection of distances provides the smallest imputation error, in particular when the number of predictors is large. In addition, the selected procedure is applied to real data from different fields.

A general framework of latent trait item response models for continuous responses is given. In contrast to classical test theory models, which traditionally distinguish between true scores and error scores, the responses are clearly linked to latent traits. It is shown that classical test theory models can be derived as special cases but the model class is much wider. It provides, in particular, appropriate modelling of responses that are restricted in some way, for example, if responses are positive or are restricted to an interval. Restrictions of this sort are easily incorporated in the modeling framework. Restriction to an interval is typically ignored in common models yielding inappropriate models, for example, when modeling Likert-type data. The model also extends common response time models, which can be treated as special cases. Properties of the model class are derived and the role of the total score is investigated, which leads to a modified total score. Several applications illustrate the use of the model including an example, in which covariates that may modify the response are taken into account.

Motivated by recent work studying massive imaging data in the neuroimaging literature, we propose multivariate varying coefficient models (MVCM) for modeling the relation between multiple functional responses and a set of covariates. We develop several statistical inference procedures for MVCM and systematically study their theoretical properties. We first establish the weak convergence of the local linear estimate of coefficient functions, as well as its asymptotic bias and variance, and then we derive asymptotic bias and mean integrated squared error of smoothed individual functions and their uniform convergence rate. We establish the uniform convergence rate of the estimated covariance function of the individual functions and its associated eigenvalue and eigenfunctions. We propose a global test for linear hypotheses of varying coefficient functions, and derive its asymptotic distribution under the null hypothesis. We also propose a simultaneous confidence band for each individual effect curve. We conduct Monte Carlo simulation to examine the finite-sample performance of the proposed procedures. We apply MVCM to investigate the development of white matter diffusivities along the genu tract of the corpus callosum in a clinical study of neurodevelopment.

CLS a n alternative t o t h e indirect kernel method in discriminunt analysis are considered. It is shown t h a t direct kernels may be based on a n y kernel function known in discrete density estimation. The choice of smoothing parameters is bnaed on general loss function8 and a family of h a functiona which are specific for the discrimination problem is introduced. Examples with distance dependent and distance independent arnoothing parameters are given to illustrate the applicability.

Regularisation has become an important tool in statistical modelling. In particular the challenge of high dimensional data boosted the fitting of more and more complex models that can not be fitted without appropriate regularisation. The need for regularisation, however, is not restricted to the modelling of high dimensional data, it is mainly driven by the complexity of the model. When the model includes nonparametric function estimation regularisation restricts the class of functions that are fitted. In regression and classification complexity of the model is usually determined by the structuring of the predictor. Regularisation helps to identify the relevant parts, which can consist of simple linear terms, functions, parametric or nonparametric interaction terms, or complex spatially and temporally structured terms. Regularisation can be made explicit by using penalty terms that restrict estimates or can be implicitly determined by the algorithm as for example in boosting methods. This issue of Statistics and Computing collects ten papers that focus on regularisation methods in different areas and with different methodology. Two papers are devoted to the extension of boosting techniques. In the paper "Twin Boosting: Improved Feature Selection and Prediction" P. Bühlmann and T. Hothorn propose a boosting method that consists of two rounds of common boosting with the second boosting process being forced to resemble the first round of boosting. The method shows much better feature selection behaviour than common boosting, in particular as far as false positives are concerned. The paper "Estimation and Regularization Techniques for Regression Models with Multidimensional Prediction Functions

The movement of people from one place to another is getting faster and wider, this is indicated by the large number of residents who are not native to a certain area but live and settle in that area for a long time. These residents are called non-permanent residents. With the increased mobility of non-permanent residents, it is necessary to describe the condition and development of non-permanent residents as well as the availability of data on non-permanent residents in provinces, districts/cities. The Payakumbuh City Population and Civil Registration Office as the implementing agency is responsible for carrying out non-permanent population data collection. This is in accordance with Permendagri Number 14 of 2015, that Implementing Agencies are district/city government apparatus that are responsible and have the authority to carry out services in Population Administration matters. However, the implementation of Non-Permanent Population Data Collection is not easy, and has not been fully running well. This study aims to identify what are the obstacles in collecting data on non-permanent residents. The analysis carried out includes the coding stage, the concept formation stage, the categorization stage, and the theory formation stage. The findings show that external influences greatly affect the low data collection of non-permanent residents in the city of

We use the mirror coupling of Brownian motion to show that under a β ∈ (0, 1)dependent Kato type assumption 1 on the possibly nonsmooth electro-magnetic potential, the corresponding magnetic Schrödinger semigroup on an open subset of R d has a global L p -to-C 0,β Hölder smoothing property for all p ∈ [1, ∞], in particular all eigenfunctions are globally β-Hölder continuous. This results shows that the eigenfunctions of the Hamilton operator of molecule in a magnetic field are globally β-Hölder continuous under weak L q -assumptions on the magnetic potential.

The total efficiency of Magnetic Resonance Imaging (MRI) results in the need for human involvement in order to appropriately detect information contained in the image. Currently, there has been a surge in interest in automated algorithms that can more precisely divide medical image structures into substructures than prior attempts. Instant segregation of cerebral cortex width from MRI scanned images is difficult due to noise, Intensity Non-Uniformity (INU), Partial Volume Effects (PVE), MRI&#39;s low resolution, and the very complicated architecture of the cortical folds. In this paper, a Probabilistic Adaptive Cerebral Cortex Segmentation (PACCS) approach is proposed for segmenting brain areas of T1 weighted MRI of human head images. Skull Stripping (SS), Brain Hemisphere Segmentation (BHS) and CCS are the three primary processes in the suggested technique. In step 1, Non-Brain Cells (NBC) is eliminated by a Contour-Based Two-Stage Brain Extraction Method (CTS-BEM). Step 2 details ...

Amounts of residual wastes, such as plastics, paper, and textiles, in urban areas have drastically increased over the years, which hence requires sustainable waste management schemes. Refuse derived fuel (RDF) provides a solution in addressing minimizing waste disposal in landfills and providing energy, particularly in developing nations. In this study, waste-to-energy (WtE) potential from residual wastes in Baguio City was assessed. With an experimental value of 13.738 MJ/kg, it revealed a percentage error of 20.748% when compared with predicted values from an energy regression model. However, ANOVA results revealed that the energy, moisture, and ash content were all statistically comparable to reports across RDF-related studies.

The purpose of this study is to find out what potential sectors need to be developed in OKU Regency and find out the relationship between OKU District and the surrounding Regencies/Cities to support its economic growth. The results of this study indicate that in the period 2010-2016, there are 9 potential sectors that need to be developed in OKU Regency, namely the Agriculture, Forestry and Fisheries Sector; Water Supply, Waste Management, Waste and Recycling Sector; Wholesale and Retail Trade Sector, Car and Motorcycle Repair; Sector of Providing Accommodation and Foods and Drinks; Financial Services and Insurance Sector; Real Estate Sector; Education Services Sector; Health Services Sector and Social Activities; Other service sectors. Based on gravity analysis, the Regency with the most interaction with OKU Regency is Muara Enim Regency and the weakest interaction is Ogan Ilir Regency. The connection of Muara Enim Regency and OKU Regency is the biggest because the two regions have...

Recently, Bowling and Lovegrove (I 980} presented data on the persistence of sine wave gratings varying in spatial frequency and exposure duration. Persistence was measured as the blank interstimulus interval (lSI), which when alternated with the grating, produced a criterion judgment of a gap between presentations of the grating. For each spatial frequency (I, 4, and 12 cpd), persistence decreased linearly with a slope of approximately -.75 as duration increased for short durations. For longer stimulus durations, the rate of decline in persistence with increasing duration was reduced, the slope being approximately -.13. The authors fitted two linear regression lines by the method of least squares to the data points for each spatial frequency. They do not report whether a better fit could be obtained with a nonlinear continuous function, but the case for the two-limb linear function is made in terms of the change in function occurring at approximately the critical duration obtained using threshold measures of critical duration with increasing spatial frequency (Breitmeyer & Ganz, 1977; Legge, 1978). However, the authors do note that the values of critical duration so obtained are somewhat shorter than those obtained by Legge (l978). The point of these comments is that although Bowlingand Lovegrove (1980) develop a plausible case for their analysis, it is not wholly convincing and another interpretation is possible. The purpose of the present note is to show an alternative analysis of their results that would lead to different conclusions about the relationship among spatial frequency, stimulus duration, and persistence. Bowling and Lovegrove (1980) use lSI as their dependent variable, thereby following a precedent set by Meyer and Maguire (1977). has