[Genabel-commits] r793 - pkg/GenABEL/R

[noreply at r-forge.r-project.org]

Author: lckarssen
Date: 2011-10-09 23:38:20 +0200 (Sun, 09 Oct 2011)
New Revision: 793

Modified:
   pkg/GenABEL/R/polygenic.R
Log:
In GenABEL's polygenic(): Fixed minor typos in the documentation.


Modified: pkg/GenABEL/R/polygenic.R
===================================================================
--- pkg/GenABEL/R/polygenic.R	2011-10-08 21:46:51 UTC (rev 792)
+++ pkg/GenABEL/R/polygenic.R	2011-10-09 21:38:20 UTC (rev 793)
@@ -2,9 +2,9 @@
 #' 
 #' This function maximises the likelihood of the data under polygenic 
 #' model with covariates an reports twice negative maximum likelihood estimates 
-#' and the inverse of variance-covariance matrix at the point of ML. 
+#' and the inverse of the variance-covariance matrix at the point of ML. 
 #' 
-#' One of the major use of this function is to estimate residuals of the 
+#' One of the major uses of this function is to estimate residuals of the 
 #' trait and the inverse of the variance-covariance matrix for 
 #' further use in analysis with \code{\link{mmscore}} and 
 #' \code{\link{grammar}}.
@@ -17,7 +17,7 @@
 #' the residual where both the effect of covariates AND the estimated 
 #' polygenic effect (breeding values) are factored out. This thus 
 #' provides an estimate of the trait value contributed by environment
-#' (or, turning this other way around, the part of trait not explained 
+#' (or, turning this other way around, the part of the trait not explained 
 #' by covariates and by the polygene). Polygenic residuals are estimated 
 #' as
 #' 
@@ -35,21 +35,21 @@
 #' It can also be used for heritability analysis.
 #' If you want to test significance of heritability, 
 #' estimate the model and write down 
-#' the function minimum reported at "h2an" element of the output 
-#' (this is twice negative MaxLikleihood). Then do next round of 
-#' estimation, but set fixh2=0. The difference between you function minima 
-#' gives a test distribued as chi-squared with 1 d.f.
+#' the function minimum reported at the "h2an" element of the output 
+#' (this is twice the negative MaxLikelihood). Then do a next round of 
+#' estimation, but set fixh2=0. The difference between your function minima 
+#' gives a test distributed as chi-squared with 1 d.f.
 #' 
-#' The way to compute the likleihood is partly based on 
+#' The way to compute the likelihood is partly based on 
 #' the paper of Thompson (see refs), namely instead of 
-#' taking inverse of var-cov matrix every time, 
+#' taking the inverse of the var-cov matrix every time, 
 #' eigenvectors of the inverse of G (taken only once) 
 #' are used.
 #' 
 #' 
-#' @param formula Formula describing fixed effects to be used in analysis, e.g. 
+#' @param formula Formula describing fixed effects to be used in the analysis, e.g. 
 #' y ~ a + b means that outcome (y) depends on two covariates, a and b. 
-#' If no covariates used in analysis, skip the right-hand side of the 
+#' If no covariates used in the analysis, skip the right-hand side of the 
 #' equation.
 #' @param kinship.matrix Kinship matrix, as provided by e.g. ibs(,weight="freq"), 
 #' or estimated outside of GenABEL from pedigree data.
@@ -61,12 +61,12 @@
 #' rest of MLEs and var.-cov. matrix.
 #' @param starth2 Starting value for h2 estimate
 #' @param trait.type "gaussian" or "binomial"
-#' @param opt.method "nlm" or "optim". These two use dirrerent optimisation functions. 
-#' We suggest using the default \code{\link{nlm}}, though 
+#' @param opt.method "nlm" or "optim". These two use different optimisation functions. 
+#' We suggest using the default \code{\link{nlm}}, although 
 #' \code{\link{optim}} may give better results in some situations
 #' @param scaleh2 Only relevant when "nlm" optimisation function is used. 
 #' "scaleh2" is the heritability 
-#' scaling parameter, regulating how "big" are parameter changes in h2 with the 
+#' scaling parameter, regulating how "big" are parameter changes in h2 with
 #' respect to changes in other parameters. As other parameters are estimated 
 #' from previous regression, these are expected to change little from the 
 #' initial estimate. The default value of 1000 proved to work rather well under a 
@@ -75,7 +75,7 @@
 #' @param steptol steptal parameter of "nlm"
 #' @param gradtol gradtol parameter of "nlm" 
 #' @param optimbou fixed effects boundary scale parameter for 'optim'
-#' @param fglschecks additional check for convergance on/off (convergence 
+#' @param fglschecks additional check for convergence on/off (convergence 
 #' between estimates obtained and that from FGLS)
 #' @param maxnfgls number of fgls checks to perform
 #' @param maxdiffgls max difference allowed in fgls checks 
@@ -132,7 +132,7 @@
 #' singularities, or rather use \code{\link{check.marker}} for identification 
 #' of twin samples. Take special care in interpretation.
 #' 
-#' If a trait (no covarites) is used, make sure that the order of IDs in the
+#' If a trait (no covariates) is used, make sure that the order of IDs in the
 #' kinship.matrix is exactly the same as in the outcome
 #' 
 #' Please note that there is alternative to 'polygenic',