Package index • sommer

All functions

A.mat(): Additive relationship matrix
APY(): Construct an APY Relationship Precision Matrix
D.mat(): Dominance relationship matrix
GWAS(): Genome wide association study analysis
vs(): variance structure specification
vsr(): variance structure specification
summary(<mmer>): summary form a GLMM fitted with mmer
E.mat(): Epistatic relationship matrix
H.mat(): Combined relationship matrix H
MNR(): Multivariate Newton-Raphson algorithm
anova(<mmes>): anova form a GLMM fitted with mmes
antem(): Antedependence covariance structure
ar1m(): First-order autoregressive covariance structure
ar2m(): Second-order autoregressive covariance structure
ar3m(): Third-order autoregressive covariance structure
atm(): Selected-level diagonal covariance structure
atr(): Selected-level diagonal covariance structure for mmer and vsr
binm(): Binomial proportion response with its number of trials
car(): Proper conditional autoregressive spatial covariance structure
coef(<mmes>): coef form a GLMM fitted with mmes
corImputation(): Imputing a matrix using correlations
corgm(): General positive-definite correlation structure
covm(): Covariance Between Two Random Effects
covmatrix_mmes(): Covariance and correlation matrix of a fitted term with standard errors
covparams_mmes(): Extract native-scale covariance parameters from an mmes fit
covparams_mmes_se(): Native-scale covariance parameters and standard errors
csm(): Compound-symmetry covariance structure
csr(): User-specified covariance-component structure for mmer and vsr
dfToMatrix(): data frame to matrix
dsm(): Diagonal heterogeneous covariance structure
dsr(): Diagonal covariance structure for mmer and vsr
dsumm(): Direct sum of residual covariance structures across sections
fam(): Factor-analytic covariance structure
familym(): Different distribution families for the traits of a multi-trait model
fitted(<mmes>): fitted form a LMM fitted with mmes
fixm(): fixed indication matrix
ism(): Identity covariance structure
loadings_mmes(): Extract factor-analytic loadings from a fitted mmes model
mam() ma1m() ma2m(): Moving-average covariance structures of order one or two
maternm(): Matern spatial covariance structure
meffects_mmes(): Marker effects recovered from a fitted relationship-based term
metricm(): Distance-based (metric) spatial correlation structures
mmer(): mixed model equations for r records
mmes(): mixed model equations solver
ownm(): User-defined covariance structure
pmonitor(): plot the change of VC across iterations
plot(<mmes>): plot form a LMM plot with mmes
postPEV(): Post-fit prediction error variances and inverse coefficient matrix
postVarU(): Post-fit Sampling Covariance of BLUPs
predict(<mmes>): Predict form of a LMM fitted with mmes
r2(): Reliability
randef(): extracting random effects
residuals(<mmes>): Residuals form a GLMM fitted with mmes
rotate_back_mmes(): Back-transform rotated mmes random effects
rrm(): Reduced-rank covariance structure
sar(): Simultaneous autoregressive spatial covariance structure
scores_mmes(): Predict factor-analytic scores from a fitted mmes model
sommer: Solving Mixed Model Equations in R
spl2Dc(): Two-dimensional penalised tensor-product of marginal B-Spline basis.
spl2Dmats(): Get Tensor Product Spline Mixed Model Incidence Matrices
stackTraits(): Stack several trait columns into the long format used by multi-trait models
strm(): Covariance structure spanning several random terms
summary(<mmes>): summary form a GLMM fitted with mmes
toeplitzm(): General positive-definite Toeplitz correlation structure
tpsmmbwrapper(): Get Tensor Product Spline Mixed Model Incidence Matrices
unsm(): unstructured indication matrix
usm(): Unstructured positive-definite covariance structure
usr(): Unstructured covariance structure for mmer and vsr
vcc vcParams: Equality and scaling constraints between variance parameters
vpredict(): vpredict form of a LMM fitted with mmes
vsm(): Variance-structure model with arbitrary Kronecker covariance factors
wald_mmes(): Wald tests for fixed effects with optional small-sample denominator df