Package: BSagri 0.1-10

Frank Schaarschmidt

BSagri: Safety Assessment in Agricultural Field Trials

Collection of functions, data sets and code examples for evaluations of field trials with the objective of equivalence assessment.

Authors:Frank Schaarschmidt

BSagri_0.1-10.tar.gz
BSagri_0.1-10.tar.gz(r-4.5-noble)BSagri_0.1-10.tar.gz(r-4.4-noble)
BSagri_0.1-10.tgz(r-4.4-emscripten)BSagri_0.1-10.tgz(r-4.3-emscripten)
BSagri.pdf |BSagri.html
BSagri/json (API)

# Install 'BSagri' in R:
install.packages('BSagri', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • Brachycera - Eklektor counts of Brachycera
  • Cica1 - Catches of Planthoppers and Leafhoppers
  • Cica2 - Catches of Planthoppers and Leafhoppers
  • CountRep - Simulated count data incl. repeated measurements
  • Decomp - A simulated data set
  • Diptera - Soil eklektor data for some families of Diptera
  • ExNBCov - Simulated example data, drawn from a Negative Binomial Distribution
  • ExPCov - Simulated example data following a Poisson distribution
  • Feeding - Pupation and Hatching rate in a feeding experiment with four varieties
  • Lepi - Insect counts of 12 Species
  • MM1 - Simulated data set for a simple mixed model
  • MMPois - Simulated data for a simple mixed model with Poisson response
  • MMPoisRep - Simulated data for a simple mixed model with Poisson response
  • Nematocera - Trap counts of Nematocera
  • fakeln - A simulated data set of lognormal data

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

27 exports 1 stars 1.00 score 28 dependencies 3 mentions 33 scripts 198 downloads

Last updated 6 years agofrom:898d87e49e. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 01 2024
R-4.5-linuxOKSep 01 2024

Exports:allignmentBOOTSimpsonDBOOTSimpsonRc2compnamesCCDiffCCDiff.bootCCDiff.defaultCCRatioCCRatio.bootCCRatio.defaultCIGLMCInpCInp.bugsCInp.CCDiffCInp.CCRatioCInp.defaultIAcontrastsIAcontrastsCMATminus2slashSCSnpSCSnp.bugsSCSnp.CCDiffSCSnp.CCRatioSCSnp.defaultsimplesimintUnlogCIUnlogCI.glht

Dependencies:abindbootcodacodetoolsgamlssgamlss.datagamlss.distlatticemagicMASSMatrixMatrixModelsmcmcMCMCpackMCPANmratiosmultcompmvtnormnlmeplyrquantregRcppsandwichSparseMsurvivalsurvPresmoothTH.datazoo

Readme and manuals

Help Manual

Help pageTopics
Allignment according to one factorallignment
Simultaneous confidence intervals for Simpson indicesBOOTSimpsonD BOOTSimpsonR
Eklektor counts of BrachyceraBrachycera
Define row names of a contrast matrix, depending on its column namesc2compnames
Catches of Planthoppers and LeafhoppersCica1
Catches of Planthoppers and LeafhoppersCica2
Wrapper to compute confidence intervals from glmsCIGLM
Construct local confidence intervals from joint empirical distribution.CInp CInp.bugs CInp.CCDiff CInp.CCRatio CInp.default
Simulated count data incl. repeated measurementsCountRep
A simulated data setDecomp
Soil eklektor data for some families of DipteraDiptera
Simulated example data, drawn from a Negative Binomial DistributionExNBCov
Simulated example data following a Poisson distributionExPCov
A simulated data set of lognormal datafakeln
Pupation and Hatching rate in a feeding experiment with four varietiesFeeding
Interaction contrasts for 2-factorial designsIAcontrasts
Interaction contrasts for a two-factorial designIAcontrastsCMAT
Insect counts of 12 SpeciesLepi
Simulated data set for a simple mixed modelMM1
Simulated data for a simple mixed model with Poisson responseMMPois
Simulated data for a simple mixed model with Poisson responseMMPoisRep
Trap counts of NematoceraNematocera
Plot confidence intervals calculated by pairwiseCIplotCI.simplesimint plotCI.UnlogCI
Simultaneous confidence sets from empirical joint distribution.SCSnp SCSnp.bugs SCSnp.CCDiff SCSnp.CCRatio SCSnp.default
Simultaneous confidence intervals from raw estimatessimplesimint
Detailed print out for simplesimint objectssummary.simplesimint
Transform confidence intervals from glm fits.UnlogCI UnlogCI.glht
Extract variance covariance matrix from objects of class gamlssvcov.gamlss
Extract variance covariance matrix from objects of class geeglmvcov.geeglm