Scale Mixture of Skew-Normal Linear Mixed Models
Autocorrelation function for smn.lmm or smsn.lmm residuals
Extract confidence intervals from lmmBoot object
Parametric bootstrap for SMSN/SMN objects
Extracts criteria for model comparison of SMSN/SMN/SMNclmm objects
Error scale matrix associated with times
Extract smn.lmm fitted values
Extract smn.clmm fitted values
Extract smsn.lmm fitted values
Healy-type plot from a smn.lmm or smsn.lmm object
Control options for smsn.lmm(), smn.lmm() and smn.clmm()
Likelihood-ratio test for SMSN/SMN objects
Mahalanobis distance from a smn.lmm or smsn.lmm object
Mahalanobis distance from a smn.clmm object
Plot ACF for smn.lmm or smsn.lmm residuals
Plot Mahalanobis distance for a fitted smn.lmm or smsn.lmm
Plot Mahalanobis distance for a fitted smn.clmm
Plot a smn.lmm or smsn.lmm object
Plot a smn.clmm object
Prediction of future observations from an smn.lmm object
Prediction of future observations from an smn.clmm object
Prediction of future observations from an smsn.lmm object
Print a smn.lmm object
Print a smn.clmm object
Print a smsn.lmm object
Extract random effects from smsn.lmm, smn.lmm and smn.clmm objects
Extract model residuals from smn.lmm and smsn.lmm objects
Extract model residuals from smn.clmm objects
Generate data from SMSN-CLMM with censored responses
Generate data from SMSN-LMM
ML estimation of scale mixture of normal linear mixed models with cens...
ML estimation of scale mixture of normal linear mixed models
ML estimation of scale mixture of skew-normal linear mixed models
Summary of a smn.lmm object
Summary of a smn.clmm object
Summary of a smsn.lmm object
Update for SMSN/SMN/SMNclmm objects
It fits scale mixture of skew-normal linear mixed models using an expectation–maximization (EM) type algorithm, including some possibilities for modeling the within-subject dependence. Details can be found in Schumacher, Lachos and Matos (2021) <doi:10.1002/sim.8870>.
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