gammmbest_fit: Title

In kschmaus/gammmbest: Method Of Moments Based Estimation for Generalized Additive Mixed Models

Description

Description.

Usage

gammmbest_fit(x, y, group, family, fixef_index, ranef_index, cov_supp,
  alpha = 0)

Arguments

x	A design matrix.
y	A vector of response observation.
group	A character vector describing grouping of random effects.
fixef_index	An integer vector specifying which columns of x have fixed effects coefficients.
ranef_index	An integer vector specifying which columns of x have random effects coefficients.
cov_supp	An integer matrix encoding weight sharing in the prior prior's covariance matrix.
alpha	The elasticnet mixing parameter, with 0 ≤ α ≤ 1. The penalty is defined as (1-α)/2 ||Γ β||_2^2 + α ||Γ||_1 where Σ^{-1} = Γ^T Γ and Σ is the prior covariance.

Details

hello said kyle

Value

An object of class gammmbest containing

beta	The estimated coefficients for the fixed effects.
dispersion	The estimated dispersion of the model.
prior_cov	The estimated covariance of the random effects prior.
ranef	The posterior estimate of the random effects coefficients.

Examples

print("hello world")

kschmaus/gammmbest documentation built on May 7, 2019, 9 p.m.