Package index • BreedingR

Fitting a model

One engine; the formula terms choose the model.

model(): Fit a mixed model by AI-REML
model_mt(): Fits a multi-trait mixed model by AI-REML
model_ar1(): Fits a model with AR(1)/CAR(1) residual by AI-REML
gibbs(): Gibbs sampler for a single-trait mixed model
model_threshold(): Fit a threshold model for an ordered categorical trait
model_survival(): Fit a Weibull proportional hazards frailty model
survival_split(): Elementary survival records from subjects and covariate changes
suggest_model(): Suggest model terms from the shape of the data

solutions(): Breeding values, their standard error and accuracy, in one table
ebv(): Genetic values of a group
accuracy(): Accuracy of the genetic values
coef(<breeding_fit>): Coefficients of a fit: variance components or fixed-effect solutions
h2(): Heritability from the estimated components
t2(): Total heritable variance and T2 of a model with indirect genetic effects
rg(): Genetic correlation between two traits, from the multi-trait fit
h2_curve(): Heritability along the gradient, for a reaction-norm fit
h2_observed(): Heritability on the observed scale from the liability scale
h2_liability(): Heritability on the liability scale from the observed scale
se_function(): Standard error of a function of the variance components (delta method)
profile_theta(): Profile likelihood for one variance component
predict(<breeding_fit_thr>): Per-category probabilities from a threshold fit
predict(<breeding_fit_surv>): Relative risks and survival probabilities from a survival fit

Residuals of a fit and convergence of a chain.

residuals(<breeding_fit>) fitted(<breeding_fit>) residuals(<breeding_fit_ar1>) fitted(<breeding_fit_ar1>) residuals(<breeding_fit_mt>) fitted(<breeding_fit_mt>) residuals(<breeding_gibbs>) fitted(<breeding_gibbs>) residuals(<breeding_fit_thr>) residuals(<breeding_fit_surv>): Residuals and fitted values of a mixed-model fit
residual_diagnostics(): Residual diagnostics of a mixed-model fit
mcmc_diagnostics(): MCMC convergence diagnostics
as_draws_array(<breeding_gibbs>) as_draws(<breeding_gibbs>) as.mcmc.list(<breeding_gibbs>): Convert the chains of a gibbs() fit to posterior or coda draws
ess(): Effective sample size by the initial monotone sequence estimator
rhat(): Rank-normalized split R-hat
geweke_z(): Geweke convergence z-score

pedigree(): Sort a pedigree and compute inbreeding
sire_mgs(): Declare a pedigree of sires and maternal grandsires
a_inverse(): Inverse of the relationship matrix, by Henderson
a22_inverse(): Inverse of A22 by the sparse Schur complement
dominance_matrix(): Dominance relationship matrix from a pedigree
dominance_inverse(): Sparse inverse of the dominance relationship matrix, by sire x dam subclasses
partial_a(): Partial relationship matrices for a multibreed pedigree
estimate_gamma(): Estimate the relationships among metafounders from genotypes

Relationship matrices from markers and the single step.

g_matrix(): Genomic relationship matrix (VanRaden)
g_dominance(): Genomic dominance relationship matrix (Vitezica)
g_epistasis(): Additive-by-additive epistatic relationship matrix
g_epistasis_ad() g_epistasis_dd() g_epistasis_order(): Mixed and higher-order epistatic relationship matrices
genomic_inbreeding(): Genomic inbreeding from marker homozygosity
h_inverse(): Inverse of the single-step relationship matrix H
apy_inverse(): Inverse of G by the APY algorithm
apy_core_select(): Choose the APY core by the eigenvalues of G
vecchia_inverse(): Inverse of G by the Vecchia recursion
snp_blup(): Single-step SNP-BLUP: markers as equations, no G, conjugate gradients
snp_effects(): Backsolve SNP effects from a single-step fit
pegs(): Fast multi-trait genomic prediction by randomized Gauss-Seidel (PEGS)

indirect_residual(): Estimate the pen-size heterogeneous residual of the associative model
associative_matrix(): Residual covariance structure of the associative model
competition_strength(): Competitive ability from grouped contests (Bradley-Terry / Plackett-Luce)

read_plink(): Read PLINK genotypes into the genotypes= shape
read_blupf90_snp(): Read a BLUPF90 genotype file into the genotypes= shape
qc_phenotypes(): Phenotype quality control
qc_genotypes(): Genotype quality control
parentage_check(): Parent-offspring conflicts between the genotypes and the pedigree
describe(): Descriptive statistics before the fit
fst(): Per-marker Fst between groups (Weir & Cockerham)
roh(): Runs of homozygosity: F_ROH per animal and per-marker frequency

sparse_chol(): Sparse Cholesky of a symmetric positive-definite matrix
sparse_solve(): Solve A x = b with A sparse symmetric positive-definite
selected_inverse(): Takahashi selective inverse
inv_pd(): Inverse of a symmetric positive-definite matrix, by block Cholesky
br_threads(): Number of threads for the parallel parts of the engine
br_version(): Package version

Exported so that the tests can compare the two routes of the likelihood.

eval_internal(): Evaluate -2logL, score and AI at a given theta, by both routes
eval_internal_mt(): Internal multi-trait evaluation, for the gates
eval_internal_ar1(): Internal AR(1) evaluation, for the gates