Add to ORKGpackage for analysis of count time series following generalized linear models D iscussion P ape
peer reviewedThe dynamic generalized linear model for non-normal data is extended for use in repeate...
The R package tscount provides likelihood-based estimation methods for analysis and modeling of coun...
paired comparisons, ranking models, generalized linear models, Bradley-Terry models, Thurstone-Moste...
The R package tscount provides likelihood-based estimation methods for analysis and modeling of coun...
The R package tscount provides likelihood-based estimation methods for analysis and modelling of co...
This paper considers the problem of extending the classical moving average models to time series wit...
SIGLEAvailable from British Library Document Supply Centre-DSC:DXN036752 / BLDSC - British Library D...
A recursive estimation method for time series models following generalized linear models is studied ...
<p>Generalized Linear Models indicating the predictors for each measure of model performance.</p
<p>Results from generalized linear model analysis (Type 2 Diabetes Mellitus).</p
Integer‐valued time series data appear in several diverse applications. However, modeling and infere...
The estimation of data transformation is very useful to yield response variables satisfying closely ...
This paper, taken from Benjamin, Rigby and Stasinopoulous (2003), presents and examines an extension...
<p>Results from the generalized linear mixed model analysis of growth patterns.</p
Continuing to emphasize numerical and graphical methods, An Introduction to Generalized Linear Model...
peer reviewedThe dynamic generalized linear model for non-normal data is extended for use in repeate...
The R package tscount provides likelihood-based estimation methods for analysis and modeling of coun...
paired comparisons, ranking models, generalized linear models, Bradley-Terry models, Thurstone-Moste...
The R package tscount provides likelihood-based estimation methods for analysis and modeling of coun...
The R package tscount provides likelihood-based estimation methods for analysis and modelling of co...
This paper considers the problem of extending the classical moving average models to time series wit...
SIGLEAvailable from British Library Document Supply Centre-DSC:DXN036752 / BLDSC - British Library D...
A recursive estimation method for time series models following generalized linear models is studied ...
<p>Generalized Linear Models indicating the predictors for each measure of model performance.</p
<p>Results from generalized linear model analysis (Type 2 Diabetes Mellitus).</p
Integer‐valued time series data appear in several diverse applications. However, modeling and infere...
The estimation of data transformation is very useful to yield response variables satisfying closely ...
This paper, taken from Benjamin, Rigby and Stasinopoulous (2003), presents and examines an extension...
<p>Results from the generalized linear mixed model analysis of growth patterns.</p
Continuing to emphasize numerical and graphical methods, An Introduction to Generalized Linear Model...
peer reviewedThe dynamic generalized linear model for non-normal data is extended for use in repeate...
The R package tscount provides likelihood-based estimation methods for analysis and modeling of coun...
paired comparisons, ranking models, generalized linear models, Bradley-Terry models, Thurstone-Moste...