chooseModel

Using p-values from hypothesis tests, determines the set of significant 
 terms, taking into account the hierarchy or marginality of terms. 
 In particular, a term will not be tested if it is marginal to (or nested in) one 
 that is significant. 
 For example, if A:B is significant, then neither A nor B will be tested. 
 The tests conducted in choosing selected model are listed in 
 a summary <code><a href="/link/data.frame?package=asremlPlus&version=4.4.48" data-mini-rdoc="asremlPlus::data.frame">data.frame</a></code>.

htest

Assists in automating the selection of terms to include in mixed models when
'asreml' is used to fit the models. Procedures are available for choosing models that
conform to the hierarchy or marginality principle, for fitting and choosing between
two-dimensional spatial models using correlation, natural cubic smoothing spline and
P-spline models. A history of the fitting of a sequence of models is kept in a data frame.
Also used to compute functions and contrasts of, to investigate differences between and
to plot predictions obtained using any model fitting function. The content falls into
the following natural groupings: (i) Data, (ii) Model modification functions, (iii) Model
selection and description functions, (iv) Model diagnostics and simulation functions,
(v) Prediction production and presentation functions, (vi) Response transformation
functions, (vii) Object manipulation functions, and (viii) Miscellaneous functions
(for further details see 'asremlPlus-package' in help). The 'asreml' package provides a
computationally efficient algorithm for fitting a wide range of linear mixed models using
Residual Maximum Likelihood. It is a commercial package and a license for it can be
purchased from 'VSNi' <https://vsni.co.uk/> as 'asreml-R', who will supply a zip file
for local installation/updating (see <https://asreml.kb.vsni.co.uk/>). It is not needed
for functions that are methods for 'alldiffs' and 'data.frame' objects. The package
'asremPlus' can also be installed from <http://chris.brien.name/rpackages/>.

Chris Brien

asremlPlus

Augments 'ASReml-R' in Fitting Mixed Models and Packages
Generally in Exploring Prediction Differences

chooseModel function

<dl> <dt>object</dt>
<dd>an object using which p-values can be obtained for use in model selection.</dd> <dt>...</dt>
<dd>further arguments passed to or from other methods.</dd></dl>

Arguments

Author

Using p-values from hypothesis tests, determines the set of significant 
 terms, taking into account the hierarchy or marginality of terms. 
 In particular, a term will not be tested if it is marginal to (or nested in) one 
 that is significant. 
 For example, if A:B is significant, then neither A nor B will be tested. 
 The tests conducted in choosing selected model are listed in 
 a summary <code><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></code>.

Determines the set of significant terms using p-values and records the tests performed in a 
       data.frame, taking into account the 
       marginality relations of terms. — chooseModel

<dl>

 <dt>object</dt>
<dd>an object using which p-values can be obtained for use in model selection.</dd>

 <dt>...</dt>
<dd>further arguments passed to or from other methods.</dd>

</dl>

Determines the set of significant terms using p-values and records the tests performed in a 
 <code><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></code>, taking into account the 
 marginality relations of terms.

Determines the set of significant terms using p-values and records the tests performed in a 
 <code><a href="/link/data.frame?package=asremlPlus&version=4.4.48" data-mini-rdoc="asremlPlus::data.frame">data.frame</a></code>, taking into account the 
 marginality relations of terms.

chooseModel: Determines the set of significant terms using p-values and records the tests performed in a `data.frame`, taking into account the marginality relations of terms.

Description

Usage

Arguments

Author

Details

See Also