# lmeControl

0th

Percentile

##### Control Values for lme Fit

The values supplied in the function call replace the defaults and a list with all possible arguments is returned. The returned list is used as the control argument to the lme function.

Keywords
models
##### Usage
lmeControl(maxIter, msMaxIter, tolerance, niterEM, msTol,
msScale, msVerbose, returnObject, gradHess, apVar,
nlmStepMax, .relStep, natural)
##### Arguments
maxIter
maximum number of iterations for the lme optimization algorithm. Default is 50.
msMaxIter
maximum number of iterations for the nlm optimization step inside the lme optimization. Default is 50.
tolerance
tolerance for the convergence criterion in the lme algorithm. Default is 1e-6.
niterEM
number of iterations for the EM algorithm used to refine the initial estimates of the random effects variance-covariance coefficients. Default is 25.
msTol
tolerance for the convergence criterion in nlm, passed as the rel.tolerance argument to the function (see documentation on nlm). Default is 1e-7.
msScale
scale function passed as the scale argument to the nlm function (see documentation on that function). Default is lmeScale.
msVerbose
a logical value passed as the trace argument to nlm (see documentation on that function). Default is FALSE.
returnObject
a logical value indicating whether the fitted object should be returned when the maximum number of iterations is reached without convergence of the algorithm. Default is FALSE.
gradHess
a logical value indicating whether numerical gradient vectors and Hessian matrices of the log-likelihood function should be used in the nlm optimization. This option is only available when the correlation structure (corStruct
 apVar a logical value indicating whether the approximate covariance matrix of the variance-covariance parameters should be calculated. Default is TRUE. nlmStepMax stepmax value to be passed to nlm. See nlm for details. Default is 100.0 .relStep relative step for numerical derivatives calculations. Default is .Machine$double.eps^(1/3). natural a logical value indicating whether the pdNatural parametrization should be used for general positive-definite matrices (pdSymm) in reStruct, when the approximate covariance matrix of the estimators is calcul     Value a list with components for each of the possible arguments. See Also lme, nlm, optim, lmeScale Aliases lmeControl Examples library(nlme) # decrease the maximum number iterations in the ms call and # request that information on the evolution of the ms iterations be printed lmeControl(msMaxIter = 20, msVerbose = TRUE) Documentation reproduced from package nlme, version 3.1-1, License: GPL version 2 or later Community examples Looks like there are no examples yet. Post a new example:       R package Rdocumentation.org Created by DataCamp.com   Put your R skills to the test MathJax.Hub.Config({ messageStyle: "none", jax: ["input/TeX","output/CommonHTML"], extensions: ["tex2jax.js","MathMenu.js","MathZoom.js"], TeX: { extensions: ["AMSmath.js","AMSsymbols.js","noErrors.js","noUndefined.js"] }, tex2jax: { inlineMath: [ ['$','$'], ['\$','\$'] ], displayMath: [ ['$$','$$'] ], processEscapes: true, preview: 'none' } }); var$jq = jQuery.noConflict(); ;(function(p,l,o,w,i,n,g){if(!p[i]){p.GlobalSnowplowNamespace=p.GlobalSnowplowNamespace||[]; p.GlobalSnowplowNamespace.push(i);p[i]=function(){(p[i].q=p[i].q||[]).push(arguments) };p[i].q=p[i].q||[];n=l.createElement(o);g=l.getElementsByTagName(o)[0];n.async=1; n.src=w;g.parentNode.insertBefore(n,g)}}(window,document,"script","//cdn.datacamp.com/sp/2.10.2.js","snowplow")); var options = { appId: 'rdocumentation', platform: 'web', post: true, discoverRootDomain: true, contexts: { webPage: true, performanceTiming: true } }; options.forceSecureTracker = true; options.postPath = '/spevent'; window.snowplow('newTracker', 'co', "www.datacamp.com", options); window.snowplow('enableActivityTracking', 10, 10); // Ping every 10 seconds after 10 seconds window.snowplow('enableLinkClickTracking'); window.snowplow('trackPageView', null, [ { schema: 'iglu:com.datacamp/user/jsonschema/1-0-0', data: { anonId: \$jq.cookie('dc_aid'), } } ]); var config = { forms: { whitelist: ["snowplow_tracked"] }, fields: { blacklist: ['password', 'password_confirmation'] } }; window.snowplow('enableFormTracking', config); (function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function(){ (i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o), m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m) })(window,document,'script','https://www.google-analytics.com/analytics.js','ga'); ga('create', 'UA-41577880-1', 'rdocumentation.org'); ga('send', 'pageview');