Description Usage Arguments Details Value Note Author(s) References See Also Examples
mhglm
is used to fit a moment hierarchical generalized linear model.
1 2 3 4 5 6 7 8 9 10 | mhglm(formula, family = gaussian, data, weights, subset,
na.action, start = NULL, etastart, mustart, offset,
control = list(), model = TRUE, method = "mhglm.fit",
x = FALSE, z = FALSE, y = TRUE, group = TRUE,
contrasts = NULL)
mhglm.fit(x, z, y, group, weights = rep(1, nobs),
start = NULL, etastart = NULL, mustart = NULL,
offset = rep(0, nobs), family = gaussian(),
control = list(), intercept = TRUE)
|
formula, family, data, weights, subset, na.action, start, etastart,
mustart, offset, model, contrasts, intercept |
These arguments
are analogous to the similarly-named arguments for the |
control |
a list of parameters for controlling the fitting
process. For |
method |
the method to be used in fitting the model. The default
method |
x, z, y, group |
For For |
These functions are analogues of glm
and
glm.fit
, meant to be used for fitting hierarchical
generalized linear models. A typical predictor has the form
response ~ terms + (reterms | group)
where
response
is the (numeric) response vector, terms
is a
series of terms which specifies a linear predictor for
response
, reterms
is a series of terms with random
coefficients (effects), and group
is a grouping factor; observations
with the same grouping factor share the same random effects.
Currently, only one random effect term is allowed, along with a single
level of hierarchy; random effect terms of the form
reterms | g1/.../gQ
are not supported.
mhglm
returns an object of class inheriting from "mhglm"
.
The function summary
can be used to obtain or print a summary
of the results.
The generic accessor functions fixef
, ranef
,
VarCorr
, sigma
, fitted.values
and
residuals
can be used to extract various useful features of the
value returned by mhglm
.
If the moment-based random effect covariance is not positive-semidefinite, then a warning will be issued, and a projection of the estimate to the positive-semidefinite cone will be used instead.
Patrick O. Perry
Perry, P. O. (2015) "Fast Moment-Based Estimation for Hierarchical Models", Preprint.
terms.mhglm
, model.matrix.mhglm
, and
predict.mhglm
for mhglm
methods, and the
generic functions fitted.values
, residuals
,
summary
, vcov
, and weights
.
Generic functions fixef
, ranef
,
VarCorr
, and sigma
for features
related to mixed effect models.
glmer
(package lme4) for
fitting generalized linear mixed models with likelihood-based estimates.
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