rTableICC: An R Package for Random Generation of 22K and RC Contingency Tables

In this paper, we describe the R package rTableICC that provides an interface for random generation of 2 2 K and R Ccontingency tables constructed over either intraclass-correlated or uncorrelated individuals. Intraclass correlations arise in studies where sampling units include more than one individual and these individuals are correlated. The package implements random generation of contingency tables over individuals with or without intraclass correlations under various sampling plans. The package include two functions for the generation of K 2 2 tables over product-multinomial sampling schemes and that of 2 2 K tables under Poisson or multinomial sampling plans. It also contains two functions that generate R C tables under product-multinomial, multinomial or Poisson sampling plans with or without intraclass correlations. The package also includes a function for random number generation from a given probability distribution. In addition to the contingency table format, the package also provides raw data required for further estimation purposes

CryptRndTest: An R Package for Testing the Cryptographic Randomness

n this article, we introduce the R package CryptRndTest that performs eight statistical randomness tests on cryptographic random number sequences. The purpose of the package is to provide software implementing recently proposed cryptographic randomness tests utilizing goodness of-fit tests superior to the usual chi-square test in terms of statistical performance. Most of the tests included in package CryptRndTest are not available in other software packages such as the R package RDieHarder or the C library TestU01. Chi-square, Anderson-Darling, Kolmogorov-Smirnov, and Jarque-Bera goodness-of-fit procedures are provided along with cryptographic randomness tests. CryptRndTest utilizes multiple precision floating numbers for sequences longer than 64-bit based on the package Rmpfr. By this way, included tests are applied precisely for higher bit-lengths. In addition CryptRndTest provides a user friendly interface to these cryptographic randomness tests. As an illustrative application, CryptRndTest is used to test available random number generators in R

On an extended interpretation of linkage disequilibrium in genetic case-control association studies

We are concerned with statistical inference for 2 x 2 x K contingency tables in the context of genetic case-control association studies. Multivariate methods based on asymptotic Gaussianity of vectors of test statistics require information about the asymptotic correlation structure among these test statistics under the global null hypothesis. We show that for a wide variety of test statistics this asymptotic correlation structure is given by the linkage disequilibrium matrix of the K loci under investigation. Three popular choices of test statistics are discussed for illustration

A deep learning framework for prediction of crop yield in Australia under the impact of climate change

Accurate prediction of crop yields is essential to ensure food security. In this study, a new deep neural networks framework is developed to predict crop yields in Australia, considering the impact of climate change, fertilizer use, and crop area. It is implemented for oats, corn, rice, and wheat crops, and its forecasting performance is benchmarked against five statistical and machine learning methods. All the software codes for the implementation of the proposed framework are freely available. The proposed framework shows the highest forecasting performance for all the considered crop types. It provides 23%, 38%, 39%, and 40% lower average mean absolute error than the benchmark methods for oat, corn, rice, and wheat crops, respectively. The reductions in average root mean squared error are 19%, 25%, 37%, and 29% over the benchmark methods. Then, it is used to predict yields of the considered crops in Australia towards 2025 under six different climate change scenarios. It is observed that although climate change has some boosting impact on crop yield, it is not sustainable to meet the demand. However, it is possible to keep crop yields rising while mitigating climate change

rTableICC: An R Package for Random Generation of 2 x 2 x K and R x C Contingency Tables

In this paper, we describe the R package rTableICC that provides an interface for random generation of 2 x 2 x K and R x C contingency tables constructed over either intraclass-correlated or uncorrelated individuals. Intraclass correlations arise in studies where sampling units include more than one individual and these individuals are correlated. The package implements random generation of contingency tables over individuals with or without intraclass correlations under various sampling plans. The package include two functions for the generation of K 2 x 2 tables over product-multinomial sampling schemes and that of 2 x 2 x K tables under Poisson or multinomial sampling plans. It also contains two functions that generate R x C tables under product-multinomial, multinomial or Poisson sampling plans with or without intraclass correlations. The package also includes a function for random number generation from a given probability distribution. In addition to the contingency table format, the package also provides raw data required for further estimation purposes

Quality of life among Turkish immigrants in Sweden

Ojectives To assess quality of life among Turkish immigrants in Sweden by using the WHOQOL-100 scale and to evaluate the domains' contribution to explain the variance in the quality of life of the immigrants. Our hypothesis was QOL among Turkish immigrants in Sweden are better than Turkish people who are living in their home country. Materials and methods This study was performed in the districts of Stockholm where Turkish immigrants have mostly settled. With the help and guidance of the Turkish Association, a sample of 520 participants was selected. We collected the demographic data by printed questionnaires, and to measure the quality of life, we used the WHOQOL-100 scale Turkish version. For analysis, we used the SPSS V.13.0 and R package programs, variance analyses, and Bayesian regression. Results The quality of life among the sample of Turkish immigrants was found to be moderate, but higher than the sample of the Turkish population. The quality of life of male immigrants was found to be higher than for females. Swedish-born Turks had better quality of life perceptions. Conclusions Turkish immigrants' quality of life perceptions were better than those of the Turkish sample. The best scores were received from the third generation. The first generation and female immigrants need attention in order to receive higher quality of life perceptions

Bayesian estimation of log odds ratios over two-way contingency tables with intraclass correlated cells

In this article, a Bayesian approach is proposed for the estimation of log odds ratios and intraclass correlations over a two-way contingency table, including intraclass correlated cells. Required likelihood functions of log odds ratios are obtained, and determination of prior structures is discussed. Hypothesis testing for log odds ratios and intraclass correlations by using the posterior simulations is outlined. Because the proposed approach includes no asymptotic theory, it is useful for the estimation and hypothesis testing of log odds ratios in the presence of certain intraclass correlation patterns. A family health status and limitations data set is analyzed by using the proposed approach in order to figure out the impact of intraclass correlations on the estimates and hypothesis tests of log odds ratios. Although intraclass correlations are small in the data set, we obtain that even small intraclass correlations can significantly affect the estimates and test results, and our approach is useful for the estimation and testing of log odds ratios in the presence of intraclass correlations

dLagM: An R package for distributed lag models and ARDL bounds testing.

In this article, we introduce the R package dLagM for the implementation of distributed lag models and autoregressive distributed lag (ARDL) bounds testing to explore the short and long-run relationships between dependent and independent time series. Distributed lag models constitute a large class of time series regression models including the ARDL models used for cointegration analysis. The dLagM package provides a user-friendly and flexible environment for the implementation of the finite linear, polynomial, Koyck, and ARDL models and ARDL bounds cointegration test. Particularly, in this article, a new search algorithm to specify the orders of ARDL bounds testing is proposed and implemented by the dLagM package. Main features and input/output structures of the dLagM package and use of the proposed algorithm are illustrated over the datasets included in the package. Features of dLagM package are benchmarked with some mainstream software used to implement distributed lag models and ARDLs