Linear Mixed Effects Models with Non-stationary Stochastic
Processes
Fit, filter and smooth mixed models with non-stationary processes

Linear Mixed Effects Models with Non-Stationary Stochastic
Processes
Contains functions to estimate model parameters and filter, smooth and forecast random effects coefficients for mixed models with stationary and non-stationary stochastic processes under multivariate normal and t response distributions, diagnostic checks, bootstrap standard error calculation, etc.

Tests for random and fixed effects for linear mixed effect
models (lmer objects of lme4 package).
Alexandra Kuznetsova, Per Bruun Brockhoff, Rune Haubo Bojesen
Christensen
The package provides different kinds of tests on lmer
objects(of lme4 package). Tests comprise type 3 F tests for
fixed effects, LRT tests for random effects, calculation of
population means for fixed factors with confidence intervals
and corresponding plots. Package also provides backward
elimination of non-significant effects

The package provides different kinds of tests on lmer
objects (of lme4 package). The tests comprise type 3 and type 1 F tests for
fixed effects, LRT tests for random effects, calculation of
population means for fixed factors with confidence intervals
and corresponding plots. Package also provides backward
elimination of non-significant effects

R (>= 3.0.0), Matrix, stats, methods, lme4 (>= 1.0)

Tests on lmer objects (of lme4 package).
The tests comprise type 3 and type 1 F tests with approximation
methods for degrees of freedom for the
fixed effects, LR tests for the random effects, calculation of
population means for fixed factors with confidence intervals
and corresponding plots. Package also provides backward
elimination of non-significant effects

Different kinds of tests for linear mixed effects models as implemented
in 'lme4' package are provided. The tests comprise types I - III F tests
for fixed effects, LR tests for random effects.
The package also provides the calculation of population means for fixed factors
with confidence intervals  and corresponding plots. Finally the backward
elimination of non-significant effects is implemented.