SH: version

CRAN-SUBMISSION

@@ -1,3 +1,3 @@
-Version: 4.6.14
-Date: 2022-10-16 07:32:35 UTC
-SHA: 8f084fd315fed10573a01735b0dc45254a70620e
+Version: 4.6.15
+Date: 2022-12-08 12:58:04 UTC
+SHA: 6e5b04d94c7bbe5eb57009ff98415d9ee5d9d106

DESCRIPTION

@@ -1,5 +1,5 @@
 Package: doBy
-Version: 4.6.14.9005
+Version: 4.6.15
 Title: Groupwise Statistics, LSmeans, Linear Estimates, Utilities 
 Author: Søren Højsgaard <[email protected]> and Ulrich Halekoh
     <[email protected]>

NAMESPACE

@@ -67,7 +67,7 @@ export(get_X)
 export(get_contrasts)
 export(get_fun)
 export(get_linest_list)
-export(get_restrictions)
+export(get_section)
 export(get_vartypes)
 export(get_xlevels)
 export(interaction_plot)
@@ -88,9 +88,6 @@ export(popMeans)
 export(recodeVar)
 export(recover_pca_data)
 export(renameCol)
-export(restrict_fun)
-export(restrict_fun_env)
-export(restrict_fun_sub)
 export(rle2)
 export(sampleBy)
 export(sample_by)
@@ -99,6 +96,9 @@ export(sapply_by)
 export(scale2)
 export(scaleBy)
 export(scale_by)
+export(section_fun)
+export(section_fun_env)
+export(section_fun_sub)
 export(set_covariate_val)
 export(set_xlevels)
 export(splitBy)

NEWS.md

@@ -1,3 +1,10 @@
+doBy v4.6.15 (Release date: 2022-12-08)
+=======================================
+
+Changes
+
+* `restrict_fun` renamed to `section_fun` and takes different arguments (`nms`, `vls`)
+
 doBy v4.6.14 (Release date: 2022-10-16)
 =======================================
 
@@ -27,10 +34,9 @@ doBy v4.6.11 (Release date: 2021-07-13)
 doBy v4.6.10 (Release date: 2021-04-29)
 =======================================
 
-## CHANGES
+Changes
 
 * `specialize` function removed. 
-
 * `restrict` function replaces `specialize`.
 
 
@@ -42,10 +48,10 @@ doBy v4.6.10 (Release date: 2021-04-29)
 # doBy v4.6.8 (Release date: 2020-11-10)
 =========================================
 
-* head / tail added for splitByData (a list resulting from
+* head / tail added for `splitByData` (a list resulting from
   calling splitBy)
 
-* sapplyBy / sapply_by added
+* `sapplyBy` / `sapply_by` added
 
 * subSeq works on factors now (coerces to character)
 
@@ -55,7 +61,7 @@ doBy v4.6.10 (Release date: 2021-04-29)
 
 * is_grouped added
 
-* math / mathmark dataset added.
+* `math` / `mathmark` dataset added.
 
 
 doBy v4.6.7 (Release date: 2020-07-07)
@@ -202,7 +208,7 @@ Changes:
 ===============================================
 
 * linest now accepts K=NULL, in which case K is taken to be the
-	diagonal materix
+	diagonal matrix
 * No longer Depend(s) on MASS
 * Some datasets added
 * Version 4.5-12 uploaded.
@@ -229,7 +235,7 @@ Changes:
 ===============================================
 
 * LSmeans, LSmatrix and linest functions added. (There are not yet
-	methods for nlme and survival objects but they will be added).
+	methods for `nlme` and `survival` objects but they will be added).
 * popMeans and popMatrix functions removed
 * Vignette on LSmeans added.
 * Version 4.5-10 uploaded
@@ -335,8 +341,8 @@ Changes:
 * funBy function added (documentation to be done)
 * scaleBy function added
 * Minor bug fixed in summaryBy
-* popMeans extended to mer objects
-* KRmodcomp, PBmodcomp and friends moved to the pbkrtest
+* popMeans extended to `mer` objects
+* KRmodcomp, PBmodcomp etc moved to the pbkrtest
 	package
 * Version 4.4.1 uploaded.
 
@@ -442,7 +448,7 @@ Changes:
 ===============================================
 
 * Bug in summaryBy fixed: Strata did not match their values (as
-	defined by the rh.variables). Thanks to Pascal Hirsch for pointing
+	defined by the `rh.variables`). Thanks to Pascal Hirsch for pointing
 	this out.
 * Version 4.0.2 uploaded
 
@@ -463,7 +469,7 @@ Changes:
 	the levels of the factors (it used to be that the names matched
 	the levels of the factors in reverse order).
 * The formula in splitBy can now also be a character vector.
-* which.maxn and which.minn functions added
+* `which.maxn` and `which.minn` functions added
 * Version 4.0.0 uploaded
 
 
@@ -535,15 +541,15 @@ Changes:
 2008-02-13 Søren Højsgaard <[email protected]>
 ===============================================
 
-* firstobs and lastobs functions added
+* `firstobs` and `lastobs` functions added
 * Version 2.2 uploaded
 
 
 
 2007-12-05 Søren Højsgaard <[email protected]>
 ===============================================
 
-* splitBy: Results becomes a splitByData object. Two attributes
+* splitBy: Results becomes a `splitByData` object. Two attributes
 	are added: 1) grps, which is the grouping factors coded into a
 	single variable. 2) idxvec, (a list) which holds the position of
 	each row in the original data set.
@@ -557,8 +563,6 @@ Changes:
 ===============================================
 
 * DESCRIPTION file change from Depends: Hmisc to Imports: Hmisc;
-* importFrom(Hmisc,mApply) added so that not all of Hmisc is
-	loaded.
 
 
 
@@ -629,7 +633,7 @@ Changes:
 
 * Version 1.2 built and uploaded
 * Description of codstom data updated.
-* matrix2dataFrame2 and subsAttr2 added
+* `matrix2dataFrame2` and `subsAttr2` added
 * postfix argument in summaryBy can be a list
 
 
@@ -716,8 +720,6 @@ Changes:
 2006-01-17 Søren Højsgaard <[email protected]>
 ===============================================
 
-* Function summaryBy modified to take . as lhs in formula and to
-	take idvar = ~formula
-* Functions powerBy, histBy, qqnormBy have been removed (figure
-	out how to do histBy and qqnormBy using xyplot() in lattice).
+* Function summaryBy modified to take dot (.) as lhs in formula and to
+	take `idvar = ~formula`
 

R/DATA-doby.R

@@ -7,7 +7,7 @@
 #' @description Yield and sugar percentage in sugar beets from a split plot
 #'     experiment.  Data is obtained from a split plot experiment. There are 3
 #'     blocks and in each of these the harvest time defines the "whole plot" and
-#'     the sowing time defines the "split plot". Each plot was \eqn{25 m^2} and
+#'     the sowing time defines the "split plot". Each plot was 25 square meters and
 #'     the yield is recorded in kg. See 'details' for the experimental layout.
 #'
 #' @name beets
@@ -61,7 +61,7 @@
 #' therapeutically refractory tumours. We preprocessed the data using Robust
 #' Multichip Analysis (RMA). Dataset has been truncated to the 1000 most
 #' informative genes (as selected by Wilcoxon test statistics) to simplify
-#' computation. The genes have been standardised to have zero mean and unit
+#' computation. The genes have been standardized to have zero mean and unit
 #' variance (i.e. z-scored).
 #' 
 #' The factor \code{code} defines whether there was a mutation in the p53
@@ -79,8 +79,7 @@
 #' @references Miller et al (2005, PubMed
 #'     ID:16141321)
 #'
-#' @source Dr. Chris Holmes, c.holmes at stats
-#'     dot. ox . ac .uk
+#' @source Chris Holmes, \email{c.holmes@@stats.ox.ac.uk}
 #'
 #' @keywords datasets
 #'
@@ -104,65 +103,6 @@
 "breastcancer"
 
 
-#' budworm data
-#' 
-#' Effect of Insecticide on survivial of tobacco budworms
-#' number of killed budworms exposed to an insecticidepp
-#' mortality of the moth tobacco budworm 'Heliothis virescens' for 6 doses of
-#' the pyrethroid trans-cypermethrin differentiated with respect to sex
-#'
-#' @name budworm
-#' @docType data
-#' 
-#' @format This data frame contains 12 rows and 4 columns:
-#' \describe{
-#' \item{sex:}{sex of the budworm}
-#' \item{dose:}{dose of the insecticide trans-cypermethrin in [\eqn{\mu}{mu}g]}
-#' \item{ndead:}{budworms killed in a trial}
-#' \item{ntotal:}{total number of budworms exposed per trial }
-#' }
-#'
-#' @references Venables, W.N; Ripley, B.D.(1999) Modern Applied Statistics with
-#' S-Plus, Heidelberg, Springer, 3rd edition, chapter 7.2
-#'
-#' @source Collet, D. (1991) Modelling Binary Data, Chapman & Hall, London,
-#' Example 3.7
-#'
-#' @keywords datasets
-#' @examples
-#' 
-#' data(budworm)
-#' 
-#' ## function to caclulate the empirical logits
-#' empirical.logit<- function(y, n) {
-#'    el <- log((y + 0.5) / (n - y + 0.5))
-#'    el
-#' }
-#' 
-#' 
-#' # plot the empirical logits against log-dose
-#' 
-#' log.dose <- log(budworm$dose)
-#' emp.logit <- empirical.logit(budworm$ndead, budworm$ntotal)
-#' plot(log.dose, emp.logit, type='n', xlab='log-dose', ylab='emprirical logit')
-#' title('budworm: emprirical logits of probability to die ')
-#' male <- budworm$sex=='male'
-#' female <- budworm$sex=='female'
-#' lines(log.dose[male], emp.logit[male], type='b', lty=1, col=1)
-#' lines(log.dose[female], emp.logit[female], type='b', lty=2, col=2)
-#' legend(0.5, 2, legend=c('male', 'female'), lty=c(1, 2), col=c(1, 2))
-#' 
-#' \dontrun{
-#' * SAS example;
-#' data budworm;
-#' infile 'budworm.txt' firstobs=2;
-#' input sex dose ndead ntotal;
-#' run;
-#' }
-#' 
-#' 
-"budworm"
-
 
 ##
 ## carcass
@@ -171,7 +111,7 @@
 #' Lean meat contents of 344 pig carcasses
 #' 
 #' Measurement of lean meat percentage of 344 pig carcasses together with
-#' auxillary information collected at three Danish slaughter houses
+#' auxiliary information collected at three Danish slaughter houses
 #' 
 #' @name carcass
 #' 
@@ -216,7 +156,7 @@
 
 #' Diet of Atlantic cod in the Gulf of St. Lawrence (Canada)
 #' 
-#' Stomach content data for Atlantic cod (Gadus morhua) in the Gulf of
+#' Stomach content data for Atlantic cod (\emph{Gadus morhua}) in the Gulf of
 #' St.Lawrence, Eastern Canada.  Note: many prey items were of no interest for
 #' this analysis and were regrouped into the "Other" category.
 #' 
@@ -393,11 +333,11 @@
 #' The \code{dietox} data frame has 861 rows and 7 columns.
 #'
 #' @details Data contains weight of slaughter pigs measured weekly for 12
-#'     weeks. Data also contains the startweight (i.e. the weight at week
+#'     weeks. Data also contains the start weight (i.e. the weight at week
 #'     1). The treatments are 3 different levels of Evit = vitamin E (dose: 0,
 #'     100, 200 mg dl-alpha-tocopheryl acetat /kg feed) in combination with 3
 #'     different levels of Cu=copper (dose: 0, 35, 175 mg/kg feed) in the feed.
-#'     The cumulated feed intake is also recorded. The pigs are littermates.
+#'     The cumulated feed intake is also recorded. The pigs are litter mates.
 #' 
 #' 
 #' @format This data frame contains the following columns:
@@ -596,7 +536,7 @@
 #' J. Dairy Sci. 90:5453–5467 doi:10.3168/jds.2006-821.
 #'
 #' This study was part of the Biosens project used data from the
-#' “Mælkekoens energibalance og mobilisering” project; both were
+#' “Malkekoens energibalance og mobilisering” project; both were
 #' funded by the Danish Ministry of Food, Agriculture and Fisheries
 #' and the Danish Cattle Association.
 #' 
@@ -610,18 +550,18 @@
 
 #' NIRmilk
 #' 
-#' Near infra red light (NIR) measurments are made at 152 wavelengths on 17
+#' Near infra red light (NIR) measurements are made at 152 wavelengths on 17
 #' milk samples.  While milk runs through a glass tube, infra red light is sent
 #' through the tube and the amount of light passing though the tube is measured
 #' at different wavelengths.  Each milk sample was additionally analysed for
-#' fat, lactose, protein and drymatter.
+#' fat, lactose, protein and dry matter.
 #' 
 #' @name NIRmilk
 #' @docType data
 #' @format This data frame contains 18 rows and 158 columns.  The first column
-#'     is the sample number.  The columns Xwww contains the infra red light
-#'     amount at wavelength www.  The response variables are fat, protein,
-#'     lactose and dm (drymatter).
+#'     is the sample number.  The columns `Xwww` contains the infra red light
+#'     amount at wavelength `www`.  The response variables are fat, protein,
+#'     lactose and dm (dry matter).
 #' @keywords datasets
 #' @examples
 #' 	
@@ -657,9 +597,9 @@
 
 #' Weight and size of 20 potatoes
 #' 
-#' Weight and size of 20 potatoes. Weight in grams; size in milimeter. There
+#' Weight and size of 20 potatoes. Weight in grams; size in millimeter. There
 #' are two sizes: \code{length} is the longest length and \code{width} is the
-#' shortest length across a potato. #' 
+#' shortest length across a potato.  
 #' 
 #' @name potatoes
 #' @docType data

R/by-lapplyBy.R

@@ -8,9 +8,9 @@
 #######################################################################
 #' @param formula A formula describing how data should be split.
 #' @param data A dataframe.
-#' @param FUN A function to be applied to each element in the splitted
+#' @param FUN A function to be applied to each element in the split
 #'    list, see 'Examples' below.
-#' @param ... optional arguments to FUN.
+#' @param \dots optional arguments to FUN.
 #' @param USE.NAMES Same as for `sapply`
 #' @param simplify Same as for `sapply`
 #'

R/by-lmBy.R

@@ -10,9 +10,9 @@
 #'
 #' @aliases lmBy coef.lmBy coef.summary_lmBy summary.lmBy fitted.lmBy
 #'     residuals.lmBy getBy
-#' @param formula A linear model formula object of the form y ~ x1 +
-#'     ... + xn | g1 + ... + gm.  In the formula object, y represents
-#'     the response, x1, ... ,xn the covariates, and the grouping
+#' @param formula A linear model formula object of the form
+#'     `y ~ x1 + ... + xn | g1 + ... + gm`.  In the formula object, `y` represents
+#'     the response, `x1, ..., xn` the covariates, and the grouping
 #'     factors specifying the partitioning of the data according to
 #'     which different lm fits should be performed.
 #' @param data A dataframe

R/by-scaleBy.R

@@ -52,7 +52,7 @@ scale2 <- function(x, center = TRUE, scale = TRUE){
 #' 
 ###########################################################################
 #'
-#' @param formula Variables to split data frame by, as ‘as.quoted’
+#' @param formula Variables to split data frame by, as `as.quoted`
 #'     variables, a formula or character vector.
 #' @param data A dataframe or matrix
 ##' @param center Logical, should data be centered.

R/by-splitBy.R

@@ -8,7 +8,7 @@
 #' 
 ###########################################################################
 #'
-#' @param formula Variables to split data frame by, as ‘as.quoted’
+#' @param formula Variables to split data frame by, as `as.quoted`
 #'     variables, a formula or character vector.
 #' @param data A data frame
 #' @param drop Logical indicating if levels that do not occur should