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stability - Genotype-by-Environment Interaction and Yield Stability Analysis

Analyses multi-environment trials of plant breeding, laid out in randomized complete blocks in every environment, to find genotypes that are high-yielding and stable: analyses of variance in each environment and combined; Eberhart and Russell's analysis (1966) <doi:10.2135/cropsci1966.0011183X000600010011x> and Finlay and Wilkinson's regression (1963) <doi:10.1071/AR9630742>; Wricke's ecovalence, Shukla's stability variance (1972) <doi:10.1038/hdy.1972.87> and Kang and Pham's yield-stability statistic (1991) <doi:10.2134/agronj1991.00021962008300010037x>; Kang's rank-sum and Fox's top-third ranking; Eskridge's safety-first indices (1990), Annicchiarico's reliability index (1992), Lin and Binns' superiority measure (1988) and Huehn's nonparametric statistics (1979) with tests; additive main effects and multiplicative interaction (AMMI) analysis with biplots and AMMI stability values on any number of axes; the GGE biplot with which-won-where, mean-stability and discrimination views in three scalings; and a plain-language interpretation of every result, computed from its numbers.

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quarto

6.69 score 4 stars 1 dependents 41 scripts 362 downloads

DiallelAnalysisR - Diallel Analysis, Heterosis and Related Mating Designs

Analysis of diallel crosses and related mating designs in plant breeding, from the plot data of randomized complete block experiments: Griffing's four methods and two models (Griffing, 1956 <doi:10.1071/BI9560463>), from plot data, from a published table of means or over several environments, with gca by environment and sca by environment interactions and a split of reciprocal effects into maternal and non-maternal parts (Cockerham and Weir, 1977); Hayman's analysis with the Wr-Vr graph and the components of variation (Hayman, 1954 <doi:10.1093/genetics/39.6.789>); mid-parent, better-parent and standard heterosis with t tests; Gardner and Eberhart's (1966) Analyses II and III; the partial diallel (Kempthorne and Curnow, 1961 <doi:10.2307/2527989>); line by tester analysis with proportional contributions; and the North Carolina designs I, II and III (Comstock and Robinson, 1948). Missing plots are handled by least-squares means. Results include analyses of variance, effects with standard errors, variance components and genetic ratios, plots of the effects and a biplot of the crosses, tables for papers in Word, LaTeX, HTML or Markdown, simulation of diallel data and the power of the tests for planning the number of replicates, and an interactive 'shiny' application.

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quarto

6.45 score 3 stars 63 scripts 454 downloads

bayesammi - Bayesian Estimation of the Additive Main Effects and Multiplicative Interaction Model

Bayesian estimation of the additive main effects and multiplicative interaction (AMMI) model of multi-environment trials by the Gibbs sampler of Crossa, Perez-Elizalde, Jarquin, Cotes, Viele, Liu and Cornelius (2011) <doi:10.2135/cropsci2010.06.0343>: posterior distributions of the overall mean, genotype and environment effects, singular values, genotype and environment scores (von Mises-Fisher conditionals on the constrained spheres) and error variance; several chains with burn-in and thinning; posterior summaries with highest posterior density intervals; the convergence diagnostics of Raftery-Lewis, Heidelberger-Welch and Gelman-Rubin; the AMMI biplot with highest posterior density regions for inference on genotypes and environments; least-squares AMMI; and a plain-language interpretation of every result, computed from its numbers. Beyond the article: unbalanced trials with missing plots and cells (data augmentation), environment-specific error variances, the Bayesian GGE (sites regression) model of Perez-Elizalde, Jarquin and Crossa (2012) <doi:10.1007/s13253-011-0063-9>, probabilities of superior performance and stability (Dias et al. 2022 <doi:10.1007/s00122-022-04041-y>), posterior ranks, Bayesian stability measures, predictions and the winner of every environment, model choice by DIC and WAIC with posterior predictive checks, draws for the 'posterior', 'bayesplot' and 'coda' packages, a compiled sampler, and a built-in 'shiny' application. Bayesian stability analysis: the Finlay-Wilkinson, Eberhart-Russell and Shukla models by Gibbs sampling, and the posterior distributions of classical stability indices (Wricke, Shukla, Lin-Binns, Annicchiarico, Eskridge's safety-first) and of AMMI-based indices (ASV, SIPC, EV, Za, WAAS, WAASY). Every result prints the references of its method.

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quartoopenblascppopenmp

5.68 score 32 scripts 556 downloads

mhpfilter - Modified and Fully Modified Hodrick-Prescott Filters

Decomposes macroeconomic time series into trend and cycle with the Hodrick-Prescott (HP) filter and two data-driven versions of it. The modified HP filter of McDermott (1997), assessed by Choudhary, Hanif and Iqbal (2014) <doi:10.1080/00036846.2014.894631>, chooses the smoothing parameter of every series by generalised cross-validation (as described in Coe and McDermott (1997) <doi:10.2307/3867497>). The fully modified HP filter of Hanif, Iqbal and Choudhary (2017, State Bank of Pakistan Working Paper 88) also reduces the end-point bias of the HP filter: it raises the smoothing parameter at the first and last observations, with linear or quadratic weights chosen to minimise the loss of Bloechl (2014, University of Munich Discussion Paper 2014-1). Every filter is a banded linear solve, so the searches are fast; batch processing of many series, comparisons of the filters, the filter weights, gain functions and end-point loss, simulation of trend-plus-cycle series and the power comparison of the paper, 'ggplot2' graphics, a plain-language interpretation of every result and a built-in 'shiny' application.

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quartocppopenmp

5.62 score 2 stars 211 downloads

PakPC2017 - Pakistan Population Census 2017

Provides data sets and functions for exploration of Pakistan Population Census 2017 (<http://www.pbscensus.gov.pk/>).

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5.38 score 7 stars 1 dependents 23 scripts 381 downloads

baystability - Bayesian Stability Analysis of Genotype by Environment Interaction (GEI)

Performs the general Bayesian estimation method of linear-bilinear models for genotype x environment interaction of Perez-Elizalde, Jarquin and Crossa (2012) <doi:10.1007/s13253-011-0063-9>: the additive main effects and multiplicative interaction (AMMI) model and the sites regression (SREG, GGE) model, with the data of an earlier trial as the prior (conjugate normal and von Mises-Fisher priors weighted by its replicates) or with vague priors; a compiled Gibbs sampler; posterior summaries with highest posterior density intervals; convergence diagnostics; biplots with highest posterior density regions; DIC and WAIC; a plain-language interpretation of every result; and a built-in 'shiny' application. For Bayesian stability analysis in general (regression and variance models, stability indices, probabilities of superior performance), see the package 'bayesstability'.

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quartoopenblascppopenmp

4.92 score 14 scripts 448 downloads

dmai - Divisia Monetary Aggregates Index

Builds monetary aggregates from their components by the methods of index number theory. The Divisia index of Barnett (1980) <doi:10.1016/0304-4076(80)90070-6> weights every component (currency, demand deposits, savings and time deposits, ...) by its share in the expenditure on monetary services, priced by its user cost (Barnett 1978) <doi:10.1016/0165-1765(78)90051-4>. Also gives the Fisher ideal index, a variant with simple growth rates, the simple-sum aggregate, the currency equivalent index of Rotemberg, Driscoll and Poterba (1995), the dual user-cost price index and the Divisia second moments of Barnett and Serletis (1990) <doi:10.1016/0304-4076(90)90104-2>; benchmark rates given or taken from the components (upper envelope); 'ggplot2' graphics, a plain-language interpretation of every result and a built-in 'shiny' application.

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quarto

4.70 score 1 stars 1 scripts 393 downloads

VetResearchLMM - Linear Mixed Models - An Introduction with Applications in Veterinary Research

R Codes and Datasets for Duchateau, L. and Janssen, P. and Rowlands, G. J. (1998). Linear Mixed Models. An Introduction with applications in Veterinary Research. International Livestock Research Institute.

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quarto

4.58 score 19 scripts 332 downloads

PakPC2023 - Pakistan Population Census 2023

Provides data sets and functions for exploration of Pakistan Population Census 2023 (<https://www.pbs.gov.pk/>).

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4.48 score 3 stars 4 scripts 369 downloads

PakPMICS2018 - Multiple Indicator Cluster Survey (MICS) 2017-18 Data for Punjab, Pakistan

Provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2017-18 data for Punjab, Pakistan. The results of the present survey are critically important for the purposes of SDG monitoring, as the survey produces information on 32 global SDG indicators. The data was collected from 53,840 households selected at the second stage with systematic random sampling out of a sample of 2,692 clusters selected using Probability Proportional to size sampling. Six questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; (2) a water quality testing questionnaire administered in three households in each cluster of the sample; (3) a questionnaire for individual women administered in each household to all women age 15-49 years; (4) a questionnaire for individual men administered in every second household to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and (6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household.

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4.48 score 1 stars 1 scripts 377 downloads

PakPMICS2018hh - Multiple Indicator Cluster Survey (MICS) 2017-18 Household Questionnaire Data for Punjab, Pakistan

Provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2017-18 Household questionnaire data for Punjab, Pakistan. The results of the present survey are critically important for the purposes of Sustainable Development Goals (SDGs) monitoring, as the survey produces information on 32 global Sustainable Development Goals (SDGs) indicators. The data was collected from 53,840 households selected at the second stage with systematic random sampling out of a sample of 2,692 clusters selected using probability proportional to size sampling. Six questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; (2) a water quality testing questionnaire administered in three households in each cluster of the sample; (3) a questionnaire for individual women administered in each household to all women age 15-49 years; (4) a questionnaire for individual men administered in every second household to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and (6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household (<http://www.mics.unicef.org/surveys>).

Last updated

4.00 score 146 downloads

StroupGLMM - R Codes and Datasets for Generalized Linear Mixed Models: Modern Concepts, Methods and Applications by Walter W. Stroup

R Codes and Datasets for Stroup, W. W. (2012). Generalized Linear Mixed Models Modern Concepts, Methods and Applications, CRC Press.

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glmglmmlmlmm

3.85 score 14 stars 4 scripts 249 downloads

SupMZ - Detecting Structural Change with Heteroskedasticity

Calculates the sup MZ value to detect the unknown structural break points under Heteroskedasticity as given in Ahmed et al. (2017) (<DOI: 10.1080/03610926.2016.1235200>).

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3.70 score 1 scripts 348 downloads

PakPMICS2018mn - Multiple Indicator Cluster Survey (MICS) 2017-18 Men Questionnaire Data for Punjab, Pakistan

Provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2017-18 Men questionnaire data for Punjab, Pakistan. The results of the present survey are critically important for the purposes of Sustainable Development Goals (SDGs) monitoring, as the survey produces information on 32 global Sustainable Development Goals (SDGs) indicators. The data was collected from 53,840 households selected at the second stage with systematic random sampling out of a sample of 2,692 clusters selected using probability proportional to size sampling. Six questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; (2) a water quality testing questionnaire administered in three households in each cluster of the sample; (3) a questionnaire for individual women administered in each household to all women age 15-49 years; (4) a questionnaire for individual men administered in every second household to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and (6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household (<http://www.mics.unicef.org/surveys>).

Last updated

3.70 score 353 downloads

PakPMICS2018mm - Multiple Indicator Cluster Survey (MICS) 2017-18 Maternal Mortality Questionnaire Data for Punjab, Pakistan

Provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2017-18 Maternal Mortality questionnaire data for Punjab, Pakistan. The results of the present survey are critically important for the purposes of Sustainable Development Goals (SDGs) monitoring, as the survey produces information on 32 global Sustainable Development Goals (SDGs) indicators. The data was collected from 53,840 households selected at the second stage with systematic random sampling out of a sample of 2,692 clusters selected using probability proportional to size sampling. Six questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; (2) a water quality testing questionnaire administered in three households in each cluster of the sample; (3) a questionnaire for individual women administered in each household to all women age 15-49 years; (4) a questionnaire for individual men administered in every second household to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and (6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household (<http://www.mics.unicef.org/surveys>).

Last updated

3.70 score 140 downloads

PakPMICS2018fs - Multiple Indicator Cluster Survey (MICS) 2017-18 Children Age 5-17 Questionnaire Data for Punjab, Pakistan

Provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2017-18 Children Age 5-17 questionnaire data for Punjab, Pakistan. The results of the present survey are critically important for the purposes of SDG monitoring, as the survey produces information on 32 global SDG indicators. The data was collected from 53,840 households selected at the second stage with systematic random sampling out of a sample of 2,692 clusters selected using Probability Proportional to size sampling. Six questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; (2) a water quality testing questionnaire administered in three households in each cluster of the sample; (3) a questionnaire for individual women administered in each household to all women age 15-49 years; (4) a questionnaire for individual men administered in every second household to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and (6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household.

Last updated

3.70 score 136 downloads

PakPMICS2018bh - Multiple Indicator Cluster Survey (MICS) 2017-18 Birth History of Children Questionnaire Data for Punjab, Pakistan

Provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2017-18 Household questionnaire data for Punjab, Pakistan. The results of the present survey are critically important for the purposes of SDG monitoring, as the survey produces information on 32 global SDG indicators. The data was collected from 53,840 households selected at the second stage with systematic random sampling out of a sample of 2,692 clusters selected using Probability Proportional to size sampling. Six questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; (2) a water quality testing questionnaire administered in three households in each cluster of the sample; (3) a questionnaire for individual women administered in each household to all women age 15-49 years; (4) a questionnaire for individual men administered in every second household to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and (6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household.

Last updated

3.70 score 214 downloads

eda4treeR - Experimental Design and Analysis for Tree Improvement

Provides data sets and R Codes for E.R. Williams, C.E. Harwood and A.C. Matheson (2023). Experimental Design and Analysis for Tree Improvement, CSIRO Publishing.

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3.61 score 1 dependents 27 scripts 492 downloads

PSLM2015 - Pakistan Social and Living Standards Measurement Survey 2014-15

Data and statistics of Pakistan Social and Living Standards Measurement (PSLM) survey 2014-15 from Pakistan Bureau of Statistics (<http://www.pbs.gov.pk/>).

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2.93 score 17 scripts 342 downloads

StabilityApp - Stability Analysis App for GEI in Multi-Environment Trials

Provides tools for Genotype by Environment Interaction (GEI) analysis, using statistical models and visualizations to assess genotype performance across environments. It helps researchers explore interaction effects, stability, and adaptability in multi-environment trials, identifying the best-performing genotypes in different conditions. Which Win Where!

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ammibiplotgeiggemetstability-analysis

2.70 score 1 scripts 295 downloads

gvcR - Genotypic Variance Components

Functionalities to compute model based genetic components i.e. genotypic variance, phenotypic variance and heritability for given traits of different genotypes from replicated data using methodology explained by Burton, G. W. & Devane, E. H. (1953) (<doi:10.2134/agronj1953.00021962004500100005x>) and Allard, R.W. (2010, ISBN:8126524154).

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2.70 score 4 scripts 307 downloads

ppcSpatial - Spatial Analysis of Pakistan Population Census

Spatial Analysis for exploration of Pakistan Population Census 2017 (<http://www.pbscensus.gov.pk/>). It uses data from R package 'PakPC2017'.

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2.70 score 3 scripts 387 downloads

rgsp - Repetitive Group Sampling Plan Based on Cpk

Functions to calculate Sample Number and Average Sample Number for Repetitive Group Sampling Plan Based on Cpk as given in Aslam et al. (2012) (<DOI:10.1080/00949655.2012.663374>).

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2.70 score 3 scripts 336 downloads

qccrs - Quality Control Charts under Repetitive Sampling

Functions to calculate Average Sample Numbers (ASN), Average Run Length (ARL1) and value of k, k1 and k2 for quality control charts under repetitive sampling as given in Aslam et al. (2014) (<DOI:10.7232/iems.2014.13.1.101>).

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2.70 score 3 scripts 349 downloads

PakPMICS2014Ch - Multiple Indicator Cluster Survey (MICS) 2014 Child Questionnaire Data for Punjab, Pakistan

Provides data set and functions for exploration of Multiple Indicator Cluster Survey 2014 Child questionnaire data for Punjab, Pakistan.

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2.70 score 1 stars 1 scripts 316 downloads

PakPMICS2014Wm - Multiple Indicator Cluster Survey (MICS) 2014 Women Questionnaire Data for Punjab, Pakistan

Provides data set and function for exploration of Multiple Indicator Cluster Survey 2014 Women (age 15-49 years) questionnaire data for Punjab, Pakistan.

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2.70 score 1 scripts 411 downloads

PakPMICS2014HL - Multiple Indicator Cluster Survey (MICS) 2014 Household Listing Questionnaire Data for Punjab, Pakistan

Provides data set and function for exploration of Multiple Indicator Cluster Survey 2014 Household Listing questionnaire data for Punjab, Pakistan.

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2.70 score 1 scripts 389 downloads

PakPMICS2014HH - Multiple Indicator Cluster Survey (MICS) 2014 Household Questionnaire Data for Punjab, Pakistan

Provides data set and function for exploration of Multiple Indicator Cluster Survey 2014 Household questionnaire data for Punjab, Pakistan.

Last updated

2.70 score 1 scripts 332 downloads