Updates for CRAN submission

DESCRIPTION

@@ -2,7 +2,7 @@ Package: FSA
 Title: Functions for Simple Fisheries Stock Assessment Methods
 Version: 0.8.0
 Date: 2015-10-05
-Description: Functions to peform a variety of simple fish stock assessment methods.
+Description: Functions to perform a variety of simple fish stock assessment methods.
     Detailed vignettes are available on the fishR website listed below.
 Authors@R: person("Derek","Ogle",email="derek@derekogle.com",role=c("aut","cre"))
 URL: http://derekogle.com/fishR/, https://github.com/droglenc/FSA

NEWS.md

@@ -1,6 +1,42 @@
 # FSA 0.8.0 ongoing
+* Tried submitting to CRAN.
 * Added suggests for `dunn.test` for use in `dunnTest()` (see below).
+* `agePrecision()`:  Modified.  Changed `combn()` to `utils::combn()` and `sd()` to `utils::sd()` (within an `apply()`).
+* `catchCurve()`:  Modified.  Changed `na.exclude()` to `stats::na.exclude()`.
 * `dunnTest()`: Modified.  Changed to more throughly use `dunn.test()` from `dunn.test`.  Added the `two.sided=` argument to `dunnTest()` and `dunn.test.results=` to `print.dunnTest()`.
+* `expandLenFreq()`: Modified.  Changed `runif()` to `stats::runif()`.
+* `extraSS()`: Modified.  Changed `anova()` to `stats::anova()` in an `lapply()`.
+* `fishR()`:  Modified.  Changed `browseURL()` to `utils::browseURL()`.
+* `fsaNews()`:  Modified.  Changed `browseURL()` to `utils::browseURL()`.
+* `headtail()`:  Modified.  Changed `head()` to `utils::head()` and `tail()` to `utils::tail()`.
+* `hist.bootCase()`: Modified.  Changed `hist()` to `hist.formula()`.
+* `iAgeBiasPlot()`: Modified.  Changed `grconvertY()` to `graphics::grconvertY()`.
+* `iALKMean.QD()`: Modified.  Changed `var()` to `stats::var()` (within `sumTable()`).
+* `iBubblesAdd()`: Modified.  Changed `rgb()` to `grdevices::rgb()`.
+* `iChkComplexModel()`: Modified.  Changed `df.residual()` to `stats::df.residual()`.
+* `iCIboot()`: Modified.  Changed `hist()` to `hist.formula()`.
+* `iEvent2Indiv()`: Modified.  Changed `unstack()` to `utils::unstack()`.
+* `iGetAllDependencies()`: Modified.  Changed `installed.packages()` to `utils::installed.packages()`.
+* `iHistResids()`: Modified.  Removed `graphics::hist()` and changed to `hist.formula()`.
+* `iHndlFormula()`: Modified.  Changed `terms()` to `stats::terms()`.
+* `iHndlResidType()`: Modified.  Changed `rstandard()` to `stats::rstandard()` and `rstudent()` to `stats::rstudent()`.
+* `iHtestBoot()`: Modified.  Removed `graphics::hist()` and changed to `hist.formula()`.
+* `iMakeColor()`: Modified.  Changed `rgb()` to `grdevices::rgb()`.
+* `iMakeModelHeading()`: Modified.  Changed `formula()` to `stats::formula()` (within an `lapply()`).
+* `iMoran()`: Modified.  Changed `optimize()` to `grdevices::optimize()`.
+* `iProcessSessionInfo()`: Modified.  Changed `sessioninfo()` to `utils::sessioninfo()`.
+* `iSchnute()`: Modified.  Changed `optimize()` to `grdevices::optimize()`.
+* `iTypeoflm()`: Modified.  Changed `formula()` to `stats::formula()`.
+* `plot.AgeBias()`: Modified.  Changed `rgb()` to `grdevices::rgb()`.
+* `plot.CatchCurve()`: Modified.  Changed `predict()` to `stats::predict()`.
+* `print.extraTest()`: Modified.  Changed `printCoefMat()` to `stats::printCoefMat()`.
+* `psdAdd()`:  Modified.  Changed `data()` to `utils::data()`.
+* `psdVal()`:  Modified.  Changed `data()` to `utils::data()`.
+* `reproInfo()`: Modified.  Changed `graphics.off()` to `grdevices::graphics.off()`.
+* `removal()`: Modified.  Removed some of the examples from the help page to reduce the elapsed time for CRAN.
+* `vbStarts()`: Modified.  Changed `rgb()` to `grdevices::rgb()`.
+* `wrAdd()`:  Modified.  Changed `data()` to `utils::data()`.
+* `wsVal()`:  Modified.  Changed `data()` to `utils::data()`.
 
 # FSA 0.7.11 Oct15
 * Converted all `.txt` files to `.Rda` files.  Original `.txt` files are in the `data-raw` directory which was added to `.Rbuildignore`.

R/FSA-internals.R

@@ -148,7 +148,7 @@ iHndlFormula <- function(formula,data,expNumR=NULL,
   } else {
     # More than one variable in the formula.
     # Must identify if there is a LHS.
-    ifelse(attr(terms(formula),"response")==0,LHS <- FALSE, LHS <- TRUE)
+    ifelse(attr(stats::terms(formula),"response")==0,LHS <- FALSE, LHS <- TRUE)
     # See if more than one variable on LHS
     if (LHS) {
       fcLHS <- as.character(formula)[2]
@@ -267,13 +267,13 @@ iMakeColor <- function(clr,transvalue) {
   if (transvalue <= 0) stop("'transvalue' must be greater than 0.",call.=FALSE)
   if (transvalue > 1) transvalue <- 1/transvalue
   clrprts <- grDevices::col2rgb(clr)/255
-  rgb(clrprts[1,1],clrprts[2,1],clrprts[3,1],transvalue)
+  grDevices::rgb(clrprts[1,1],clrprts[2,1],clrprts[3,1],transvalue)
 }
 
 
 iTypeoflm <- function(mdl) {
   if (any(class(mdl)!="lm")) stop("'iTypeoflm' only works with objects from 'lm()'.",call.=FALSE)
-  tmp <- iHndlFormula(formula(mdl),stats::model.frame(mdl))
+  tmp <- iHndlFormula(stats::formula(mdl),stats::model.frame(mdl))
   if (tmp$Enum==0) stop("Object must have one response and at least one explanatory variable",call.=FALSE)
   if (!tmp$Rclass %in% c("numeric","integer")) stop("Response variable must be numeric",call.=FALSE)
   if (tmp$Etype=="factor") { #ANOVA

R/FSAUtils.R

@@ -213,7 +213,7 @@ fishR <- function(where=c("home","IFAR","general","books","AIFFD","posts","news"
          AIFFD=  { tmp <- paste0(tmp,"aiffd2007") },
          posts=,news=  { tmp <- paste0(tmp,"fishR/blog") }
   )
-  browseURL(tmp)
+  utils::browseURL(tmp)
   invisible(tmp)
 }
 
@@ -242,7 +242,7 @@ fishR <- function(where=c("home","IFAR","general","books","AIFFD","posts","news"
 #' @rdname fsaNews
 #' @export
 fsaNews <- function () {
-  browseURL("https://github.com/droglenc/FSA/blob/master/NEWS.md")
+  utils::browseURL("https://github.com/droglenc/FSA/blob/master/NEWS.md")
 }
 
 #' @rdname fsaNews
@@ -305,11 +305,11 @@ headtail <- function(x,n=3L,which=NULL,addrownums=TRUE,...) {
   n <- ifelse(n<0L,max(N+n,0L),min(n,N))
   if (n>=N) tmp <- x
   else {
-    h <- head(x,n,...)
+    h <- utils::head(x,n,...)
     if (addrownums) {
       if (is.null(rownames(x))) rownames(h) <- paste0("[",1:n,",]")
     } else rownames(h) <- NULL
-    t <- tail(x,n,addrownums,...)
+    t <- utils::tail(x,n,addrownums,...)
     tmp <- rbind(h,t)
   }
   if (!is.null(which)) tmp <- tmp[,which]

R/ageComparisons.R

@@ -384,7 +384,8 @@ iEvansHoenig <- function(obj) {
 plot.ageBias <- function(x,what=c("bias","sunflower","numbers"),difference=FALSE,
                          xlab=x$ref.lab,ylab=x$nref.lab,show.n=TRUE,nYpos=1.03,cex.n=0.75,
                          lwd=1,
-                         show.pts=FALSE,pch.pts=19,col.pts=rgb(0,0,0,transparency),transparency=1/10,
+                         show.pts=FALSE,pch.pts=19,
+                         col.pts=grDevices::rgb(0,0,0,transparency),transparency=1/10,
                          pch.mean=95,cex.mean=lwd,
                          col.CI="black",col.CIsig="red",lwd.CI=lwd,sfrac=0,
                          show.range=FALSE,col.range="gray",lwd.range=lwd,
@@ -458,7 +459,7 @@ iAgeBiasPlot <- function(obj,difference,xlab,ylab,show.n,nYpos,cex.n,
     graphics::points(x=d[,1][!d$sig],y=d$mean[!d$sig],pch=pch.mean,cex=cex.mean)
   }
   # show the sample sizes at the top
-  if (show.n) graphics::text(d[,1],grconvertY(nYpos,"npc"),d$n,cex=cex.n,xpd=TRUE)
+  if (show.n) graphics::text(d[,1],graphics::grconvertY(nYpos,"npc"),d$n,cex=cex.n,xpd=TRUE)
 }
 
 #=============================================================
@@ -661,7 +662,7 @@ agePrecision <- function(formula,data) {
   ## Precision alculations (APE and ACV) on each fish
   # Mean, SD of assigned ages
   age.avg <- apply(d,1,mean)
-  age.sd <- apply(d,1,sd)
+  age.sd <- apply(d,1,stats::sd)
   # Summed absolute deviation
   tmp.adevs <- abs(apply(d,2,'-',age.avg))
   age.ad <- apply(tmp.adevs,1,sum)
@@ -682,7 +683,7 @@ agePrecision <- function(formula,data) {
 
   ## Raw age agreement summaries
   # find all pairs of comparisons
-  prs <- t(combn(names(d),2))
+  prs <- t(utils::combn(names(d),2))
   # maximum possible difference is max age - min age ... use this to set the levels
   #   for the agreement table.
   tmp <- max(d,na.rm=TRUE)-min(d,na.rm=TRUE)

R/alkPlot.R

@@ -265,7 +265,7 @@ iBubbleFindIn <- function(alsum,buf) {
 iBubblesAdd <- function(key,alsum,buf,col) {
   tmp <- iBubbleUnmatKey(key,alsum)
   with(tmp,symbols(len,age,circles=sqrt(tmp$prop),inches=iBubbleFindIn(alsum,buf),
-                   bg=col,fg=rgb(0,0,0,0.5),add=TRUE))
+                   bg=col,fg=grDevices::rgb(0,0,0,0.5),add=TRUE))
 }
 
 iALKPlotBubble <- function(key,xlab,ylab,xlim,ylim,grid,buf,col,add,...) {

R/alkSummaries.R

@@ -231,8 +231,8 @@ iALKMean.QD <- function(key,formula,data,N_i) {
   n_ij <- sumTable(formula,data,FUN=length)
   mn_ij <- sumTable(formula,data,FUN=mean)
   # Not sure from Q&D if this should be divided by sqrt(n) or not
-  var_ij <- sumTable(formula,data,FUN=var)/sqrt(sumTable(formula,data,FUN=length))
-  #var_ij <- sumTable(formula,data,FUN=var)/sqrt(sumTable(formula,data,FUN=length))
+  var_ij <- sumTable(formula,data,FUN=stats::var)/sqrt(sumTable(formula,data,FUN=length))
+  #var_ij <- sumTable(formula,data,FUN=stats::var)/sqrt(sumTable(formula,data,FUN=length))
   options(warn=0)
   ## See if key has a row that sums to zero, remove that row from
   ##   the key, N_i, n_ij, mn_ij, and var_ij

R/bootstrap.R

@@ -100,11 +100,11 @@ hist.bootCase <- function(x,same.ylim=TRUE,ymax=NULL,
   graphics::par(mfrow=c(rows,cols))
 	## If not given ymax, then find highest count on all histograms
   if (is.null(ymax)) {
-    for (i in 1:ncol(x)) ymax[i] <- max(hist(~x[,i],plot=FALSE,warn.unused=FALSE,...)$counts)
+    for (i in 1:ncol(x)) ymax[i] <- max(hist.formula(~x[,i],plot=FALSE,warn.unused=FALSE,...)$counts)
   }
   if (same.ylim) ymax <- rep(max(ymax),length(ymax))
 	## Make the plots
-	for(i in 1:ncol(x)) hist(~x[,i],xlab=colnames(x)[i],ylim=c(0,ymax[i]),...)
+	for(i in 1:ncol(x)) hist.formula(~x[,i],xlab=colnames(x)[i],ylim=c(0,ymax[i]),...)
   graphics::par(mfrow=op)
 }
 
@@ -253,7 +253,7 @@ iCIBoot <- function(object,parm,conf.level,plot,err.col,err.lwd,rows,cols,...) {
     ## Plotting depends on whether one vector or not
     if (length(parm)==1) {
       ## one histogram
-      h <- hist(~object,xlab=parm,main="")
+      h <- hist.formula(~object,xlab=parm,main="")
       plotrix::plotCI(mean(object),y=0.95*max(h$counts),li=res[1],ui=res[2],err="x",
              pch=19,col=err.col,lwd=err.lwd,add=TRUE,...)
     } else {
@@ -264,7 +264,7 @@ iCIBoot <- function(object,parm,conf.level,plot,err.col,err.lwd,rows,cols,...) {
       op <- graphics::par("mfrow")
       graphics::par(mfrow=c(rows,cols))
       for (i in 1:np) {
-        h <- hist(~object[,i],xlab=colnames(object)[i],...)
+        h <- hist.formula(~object[,i],xlab=colnames(object)[i],...)
         plotrix::plotCI(mean(object[,i]),y=0.95*max(h$counts),li=res[i,1],ui=res[i,2],err="x",
                pch=19,col=err.col,lwd=err.lwd,add=TRUE)
       }
@@ -328,7 +328,7 @@ iHTestBoot <- function(object,parm,bo,alt=c("two.sided","less","greater"),plot=F
   rownames(res) <- ""
   ## Make a plot if asked for
   if (plot) {
-    hist(~object,xlab=colnames(object),main="")
+    hist.formula(~object,xlab=colnames(object),main="")
     graphics::abline(v=bo,col="red",lwd=2,lty=2)
   }
   ## Return the result

R/capHistConvert.R

@@ -374,7 +374,7 @@ iEvent2Indiv <- function(df,id,event.ord) {
   tmp <- as.data.frame(ch.tab)
   names(tmp) <- c("id","event","freq")
   # Unstack and add rownames to data.frame
-  tmp <- unstack(tmp,freq~event)
+  tmp <- utils::unstack(tmp,freq~event)
   tmp <- data.frame(rownames(ch.tab),tmp)
   names(tmp) <- c(ifelse(is.null(id),"id",id),levels(factor(df[,event])))
   # force id to be a character (rather than a factor as from as.data.frame)

R/catchCurve.R

@@ -126,7 +126,7 @@ catchCurve.default <- function(x,catch,ages2use=age,weighted=FALSE,...) {
 
   ## Fit the model to descending limb
   log.catch.e <- log(catch.e)
-  cclm <- stats::lm(log.catch.e~age.e,na.action=na.exclude)
+  cclm <- stats::lm(log.catch.e~age.e,na.action=stats::na.exclude)
   if (weighted) {
     # if asked to fit weighted regression then find weights as
     #   the predicted values from the raw regression
@@ -139,7 +139,7 @@ catchCurve.default <- function(x,catch,ages2use=age,weighted=FALSE,...) {
       W[tmp] <- min(W[which(W>0)])
     } 
     # and then fit the weighted regression
-    cclm <- stats::lm(log.catch.e~age.e,weights=W,na.action=na.exclude)
+    cclm <- stats::lm(log.catch.e~age.e,weights=W,na.action=stats::na.exclude)
   } else {
     # if not asked to fit weighted regression then fill weights
     #   with NULL for return in the list below.
@@ -230,7 +230,7 @@ plot.catchCurve <- function(x,pos.est="topright",cex.est=0.95,
   # Highlight descending limb portion
   graphics::points(x$age.e,x$log.catch.e,col=col.pt,pch=19)
   # Put model on descending limb
-  graphics::lines(x$age.e,predict(x$lm,data.frame(x$age.e)),lwd=lwd,lty=lty,col=col.mdl)
+  graphics::lines(x$age.e,stats::predict(x$lm,data.frame(x$age.e)),lwd=lwd,lty=lty,col=col.mdl)
   # Put mortality values on the plot
   if (!is.null(pos.est)) {
     Z <- -stats::coef(x$lm)[2]

R/expandLenFreq.R

@@ -96,7 +96,7 @@ expandLenFreq <- function(x,w,additional,
   new.lens <- c(nrand.lens,rand.lens)
   # make sure that a length can't cross out of length category
   maxval <- w-1/(10^decimals)
-  if (maxval>0) new.lens <- new.lens + runif(length(new.lens),min=0,max=maxval)
+  if (maxval>0) new.lens <- new.lens + stats::runif(length(new.lens),min=0,max=maxval)
   new.lens <- round(new.lens,decimals)
   # if asked, print some summary values of what happened
   if (show.summary) {

R/extraTests.R

@@ -142,7 +142,7 @@ extraSS <- function(sim,...,com,sim.names=sim.name,sim.name=NULL,com.name=NULL)
   ## Check if complex model is actually more complex
   iChkComplexModel(sim,com)
   ## run anova for each sim and com pair
-  tmp <- lapply(sim,anova,com)
+  tmp <- lapply(sim,stats::anova,com)
   ## prepare a matrix to received the anova results
   res <- matrix(NA,nrow=n.sim,ncol=6+2)
   ## extract results from all anovas and put in results matrix
@@ -173,7 +173,7 @@ extraSS <- function(sim,...,com,sim.names=sim.name,sim.name=NULL,com.name=NULL)
 print.extraTest <- function(x,...) {
   cat(attr(x,"heading"),"\n\n")
   nms <- names(x)
-  printCoefmat(x,cs.ind=c(2,4,6),tst.ind=7,zap.ind=6,has.Pvalue=TRUE,...)
+  stats::printCoefmat(x,cs.ind=c(2,4,6),tst.ind=7,zap.ind=6,has.Pvalue=TRUE,...)
 }
 
 # ============================================================
@@ -203,7 +203,7 @@ iMakeModelHeading <- function(sim,com,sim.names,com.name) {
   if (!is.null(sim.names)) {
     if (length(sim.names)!=length(sim)) stop("Length of 'sim.names' differs from number of simple models provided.",call.=FALSE)
     sim_hdg <- paste("Model ",1:length(sim),": ",sim.names,sep="",collapse="\n")
-  } else sim_hdg <- paste("Model ",1:length(sim),": ",lapply(sim,formula),sep="",collapse="\n")
+  } else sim_hdg <- paste("Model ",1:length(sim),": ",lapply(sim,stats::formula),sep="",collapse="\n")
   ## Handle the complex model names ... if none is given (i.e.,
   ## com.name is NULL) then make from the formula of com
   if (!is.null(com.name)) {
@@ -223,7 +223,7 @@ iMakeModelHeading <- function(sim,com,sim.names,com.name) {
 #   something is sent in sim.names and com.name.
 # ============================================================
 iChkComplexModel <- function(sim,com) {
-  simDF <- unlist(lapply(sim,df.residual))
-  comDF <- df.residual(com)
+  simDF <- unlist(lapply(sim,stats::df.residual))
+  comDF <- stats::df.residual(com)
   if (!all(comDF<simDF)) warning("'com' model does not appear to be more complex than all models in 'sim'.\n  Check results carefully.",call.=FALSE)
 }

R/knitUtil.R

@@ -176,7 +176,7 @@ reproInfo <- function(out=c("r","markdown","latex"),rqrdPkgs=NULL,elapsed=NULL,
   if (out=="r") iReproInfoR(rqrdPkgs,ses,elapsed,compDate,compTime,width)
   else if (out=="latex") iReproInfoLaTeX(rqrdPkgs,ses,elapsed,compDate,compTime,addTOC,newpage)
   else iReproInfoMarkdown(rqrdPkgs,ses,elapsed,compDate,compTime,links)
-  if (closeGraphics) graphics.off()
+  if (closeGraphics) grDevices::graphics.off()
 }
 
 
@@ -196,7 +196,7 @@ iMakeFilename <- function(file,extension,directory=NULL) {
 
 iGetAllDependencies <- function(pkgs) {
   # get a list of available packages ... this is needed for package.dependencies below
-  inst <- installed.packages()
+  inst <- utils::installed.packages()
   #   isolate to the supplied packages
   inst <- inst[inst[,"Package"] %in% pkgs,]
   deps <- NULL
@@ -230,7 +230,7 @@ iProcessSessionInfo <- function() {
     pkg <- sapply(L[[n]], function(x) x[["Package"]])
     paste(pkg, vers, sep = "_")
   } # end internal mkLabel
-  ses <- sessionInfo()
+  ses <- utils::sessionInfo()
   sys <- paste(Sys.info()["sysname"],", ",ses$platform,"\n",sep="") 
   vers <- paste(ses$R.version$version.string,"\n",sep="")
   bpkgs <- sort(ses$basePkgs) 

R/psdAdd.R

@@ -99,7 +99,7 @@ psdAdd.default <- function(len,spec,units=c("mm","cm","in"),use.names=TRUE,
   }
   ## Prepare the PSD literature values data frame
   # get is used to eliminate problem with rcmd check
-  PSDlit <- get(data("PSDlit", envir = environment()), envir = environment())
+  PSDlit <- get(utils::data("PSDlit", envir = environment()), envir = environment())
 
   ## Create data.frame with length, species, rownumbers, and PSD values (blank)
   data <- data.frame(len,spec,rownums=1:length(len),PSD=rep(NA,length(len)))

R/psdVal.R

@@ -57,7 +57,7 @@ psdVal <- function(species="List",units=c("mm","cm","in"),incl.zero=TRUE,
   units <- match.arg(units)
   # load RSDlit data frame into this function's environment
   # the data/get combination are used to avoid the "no global binding" note at CHECK
-  PSDlit <- get(data("PSDlit", envir = environment()), envir = environment())
+  PSDlit <- get(utils::data("PSDlit", envir = environment()), envir = environment())
   # continue if species name is correct
   if (iPSDLitCheck(PSDlit,species <- capFirst(species))) {
     # identify columns based on units