chlm_grad: Gradient of the HLM loglikelihood.
In mlysy/hlm: Inference for a Heteroscedastic Linear Model
Description
Usage
Arguments
Value
Description
Gradient of the HLM loglikelihood.
Usage
1
Arguments
beta
Mean parameter vector of length p.
gamma
Variance parameter vector of length q.
y
Vector of observations of length n.
delta
Optional logical vector of length n indicating the censorring status (TRUE: uncensored, FALSE: uncensored).
X
Mean covariate matrix of size n x p.
Z
Variance covariate matrix of size n x q.
Value
Vector of length p+q returning the gradient of the loglikelihood at the parameter values.
mlysy/hlm documentation built on Nov. 4, 2019, 7:26 p.m.
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Description Usage Arguments Value
Description
Gradient of the HLM loglikelihood.
Usage
1 |
Arguments
beta |
Mean parameter vector of length |
gamma |
Variance parameter vector of length |
y |
Vector of observations of length |
delta |
Optional logical vector of length |
X |
Mean covariate matrix of size |
Z |
Variance covariate matrix of size |
Value
Vector of length p+q returning the gradient of the loglikelihood at the parameter values.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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