Replace 'library()' with 'require()' which is (about 5 times) faster

lbbe-software · Oct 1, 2024 · 89f00a6 · 89f00a6
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diff --git a/README.md b/README.md
@@ -41,7 +41,7 @@ remotes::install_github("lbbe-software/fitdistrplus")
 
 Finally load the package in your current R session with the following R command:
 ```r
-library(fitdistrplus)
+require("fitdistrplus")
 ```
 
 ## Documentation

diff --git a/man/bootdist.Rd b/man/bootdist.Rd
@@ -227,7 +227,7 @@ summary(bootdist(f1, niter = niter))
 proc.time() - ptm
 
 # parallel version using snow
-require(parallel)
+require("parallel")
 ptm <- proc.time()
 summary(bootdist(f1, niter = niter, parallel = "snow", ncpus = 2))
 proc.time() - ptm

diff --git a/man/bootdistcens.Rd b/man/bootdistcens.Rd
@@ -181,7 +181,7 @@ summary(bootdistcens(f1, niter = niter))
 proc.time() - ptm
 
 # parallel version using snow
-require(parallel)
+require("parallel")
 ptm <- proc.time()
 summary(bootdistcens(f1, niter = niter, parallel = "snow", ncpus = 2))
 proc.time() - ptm

diff --git a/man/fitdist.Rd b/man/fitdist.Rd
@@ -426,7 +426,7 @@ summary(res2)
     #wrap genoud function rgenoud package
     mygenoud <- function(fn, par, ...) 
     {
-        require(rgenoud)
+        require("rgenoud")
         res <- genoud(fn, starting.values=par, ...)        
         standardres <- c(res, convergence=0)
 
@@ -474,7 +474,7 @@ gofstat(fWqme)
 #
 
 \donttest{
-    require(actuar)
+    require("actuar")
     #simulate a sample
     x4 <- rpareto(1000, 6, 2)
 
@@ -565,7 +565,7 @@ quantile(fln, probs = c(0.05, 0.1, 0.2))
 
 \donttest{
 set.seed(1234)
-require(mc2d)
+require("mc2d")
 t <- rtriang(100, min=5, mode=6, max=10)
 fCvM <- fitdist(t, "triang", method="mge", start = list(min=4, mode=6,max=9), gof="CvM")
 fKS <- fitdist(t, "triang", method="mge", start = list(min=4, mode=6,max=9), gof="KS")
@@ -575,7 +575,7 @@ cdfcomp(list(fCvM,fKS))
 # (17) fit a non classical discrete distribution (the zero inflated Poisson distribution)
 #
 \donttest{
-require(gamlss.dist)
+require("gamlss.dist")
 set.seed(1234)
 x <- rZIP(n = 30, mu = 5, sigma = 0.2)
 plotdist(x, discrete = TRUE)
@@ -593,7 +593,7 @@ gofstat(list(fitzip, fitp))
 # (18) examples with distributions in actuar (predefined starting values)
 #
 \donttest{
-require(actuar)
+require("actuar")
 x <- c(2.3,0.1,2.7,2.2,0.4,2.6,0.2,1.,7.3,3.2,0.8,1.2,33.7,14.,
        21.4,7.7,1.,1.9,0.7,12.6,3.2,7.3,4.9,4000.,2.5,6.7,3.,63.,
        6.,1.6,10.1,1.2,1.5,1.2,30.,3.2,3.5,1.2,0.2,1.9,0.7,17.,

diff --git a/man/fitdistcens.Rd b/man/fitdistcens.Rd
@@ -262,7 +262,7 @@ fitdistcens(log10EC50,"logis",optim.method="SANN")
     #wrap genoud function rgenoud package
     mygenoud  <-  function(fn, par, ...) 
     {
-        require(rgenoud)
+        require("rgenoud")
         res  <-  genoud(fn, starting.values=par, ...)        
         standardres  <-  c(res, convergence=0)
             

diff --git a/man/logLik-plot.Rd b/man/logLik-plot.Rd
@@ -100,7 +100,7 @@ llplot(fitg2, fit.show = TRUE)
 \donttest{
   data(endosulfan)
   ATV <-endosulfan$ATV
-  library("actuar")
+  require("actuar")
   fBurr <- fitdist(ATV, "burr", start = list(shape1 = 0.3, shape2 = 1, rate = 1))
   llplot(fBurr)
   llplot(fBurr, back.col = FALSE, fit.show = TRUE, fit.pch = 16)

diff --git a/man/mgedist.Rd b/man/mgedist.Rd
@@ -158,7 +158,7 @@ mgedist(u,"unif",gof="KS")
 # 
 
 \donttest{
-require(mc2d)
+require("mc2d")
 set.seed(1234)
 t <- rtriang(100,min=5,mode=6,max=10)
 mgedist(t,"triang",start = list(min=4, mode=6,max=9),gof="CvM")

diff --git a/man/mmedist.Rd b/man/mmedist.Rd
@@ -199,7 +199,7 @@ mmedist(x3, "beta")
 #
 
 \donttest{
-  require(actuar)
+  require("actuar")
   #simulate a sample
   x4  <-  rpareto(1000, 6, 2)
 

diff --git a/tests/t-CIcdfplot.R b/tests/t-CIcdfplot.R
@@ -1,4 +1,4 @@
-library(fitdistrplus)
+require("fitdistrplus")
 
 nbboot <- 201
 nbboot <- 10

diff --git a/tests/t-Surv2fitdistcens.R b/tests/t-Surv2fitdistcens.R
@@ -1,4 +1,4 @@
-require(fitdistrplus)
+require("fitdistrplus")
 data("fremale")
 
 # fremale test

diff --git a/tests/t-bootdist.R b/tests/t-bootdist.R
@@ -1,4 +1,4 @@
-library(fitdistrplus)
+require("fitdistrplus")
 #We choose a low number of bootstrap replicates in order to satisfy CRAN running times constraint.
 #For practical application, we recommend to use nbboot=501 or nbboot=1001.
 
@@ -36,7 +36,7 @@ plot(b1, enhance=TRUE, rampcol=c("blue", "green"), nbgrid=15, nbcol=15)
 
 if(any(installed.packages()[, "Package"] == "actuar") && visualize)
 {
-  require(actuar)
+  require("actuar")
   set.seed(123)
   f1 <- fitdist(rburr(nsample, 2, 3, 1), "burr", start=list(shape1=10, shape2=10, rate=1))
   b1 <- bootdist(f1, niter=nbboot, silent=TRUE)
@@ -118,7 +118,7 @@ if (visualize)
 {
   if(any(installed.packages()[, "Package"] == "actuar"))
   {
-    require(actuar)
+    require("actuar")
     #simulate a sample
     x4 <- rpareto(nsample,  6,  2)
     memp <- function(x,  order)
@@ -144,7 +144,7 @@ if (visualize)
 {
   if(any(installed.packages()[, "Package"] == "actuar"))
   {
-    require(actuar)
+    require("actuar")
     data(danishuni)
 
     fdan <- fitdist(danishuni$Loss, "burr", method="mle", 
@@ -161,7 +161,7 @@ if (visualize)
 # 
 if(any(installed.packages()[, "Package"] == "mc2d"))
 {
-  require(mc2d)
+  require("mc2d")
   set.seed(1234)
   x4 <- rtriang(100,min=0,mode=4,max=20) # nsample not used : does not converge if the sample is too small
   fit4t<-fitdist(x4,dtriang,start=list(min=0,mode=4,max=20))

diff --git a/tests/t-bootdistcens.R b/tests/t-bootdistcens.R
@@ -1,4 +1,4 @@
-library(fitdistrplus)
+require("fitdistrplus")
 nbboot <- 101
 nbboot <- 11
 nsample <- 10

diff --git a/tests/t-cdfcomp.R b/tests/t-cdfcomp.R
@@ -1,4 +1,4 @@
-library(fitdistrplus)
+require("fitdistrplus")
 
 # ?cdfcomp
 visualize <- FALSE # TRUE for manual tests with visualization of results

diff --git a/tests/t-cdfcompcens.R b/tests/t-cdfcompcens.R
@@ -1,4 +1,4 @@
-library(fitdistrplus)
+require("fitdistrplus")
 
 visualize <- FALSE # TRUE for manual tests with visualization of results
 
@@ -43,7 +43,7 @@ if (visualize)
 {
   if(any(installed.packages()[,"Package"] == "actuar"))
   {
-    require(actuar)
+    require("actuar")
     data(smokedfish)
     fln <- fitdistcens(smokedfish,"lnorm")
     fll <- fitdistcens(smokedfish,"llogis")

diff --git a/tests/t-cvg-algo.R b/tests/t-cvg-algo.R
@@ -1,9 +1,7 @@
 
 if(FALSE)
 {  
-  library(fitdistrplus)
-
-
+    require("fitdistrplus")
 
   #(1) beta distribution
   #

diff --git a/tests/t-denscomp.R b/tests/t-denscomp.R
@@ -1,4 +1,4 @@
-library(fitdistrplus)
+require("fitdistrplus")
 
 # ?denscomp
 visualize <- FALSE # TRUE for manual test with visualization of plots

diff --git a/tests/t-descdist.R b/tests/t-descdist.R
@@ -1,4 +1,4 @@
-library(fitdistrplus)
+require("fitdistrplus")
 nbboot <- 100
 nbboot <- 10
 nsample <- 10

diff --git a/tests/t-detectbound.R b/tests/t-detectbound.R
@@ -1,4 +1,4 @@
-require(fitdistrplus)
+require("fitdistrplus")
 
 #case where the density returns a Not-an-Numeric value.
 detectbound("gamma", c(shape=3, scale=3), 1:10, echo=TRUE)
@@ -23,7 +23,7 @@ dgeom2 <- function(x, prob, log=FALSE)
 detectbound("geom2", c(prob=1/2), 1:10)
 
 #case where the density returns a Not-an-Numeric value for actuar package
-require(actuar)
+require("actuar")
 
 detectbound("burr", c(shape1=3, shape2=3, rate=1), 1:10)
 detectbound("llogis", c(shape=3, rate=1), 1:10)
diff --git a/tests/t-fitbench.R b/tests/t-fitbench.R
@@ -1,6 +1,6 @@
 if(FALSE)
 {  
-  require(fitdistrplus)
+  require("fitdistrplus")
 
   x <- rgamma(1e3, shape=3/2, rate= 1/2)
 

diff --git a/tests/t-fitdist-customoptim.R b/tests/t-fitdist-customoptim.R
@@ -1,5 +1,5 @@
 visualize <- FALSE # TRUE for manual tests with visualization of results
-require(fitdistrplus)
+require("fitdistrplus")
 
 myoptimize <- function(fn,par,ui,ci,...){
   res <- constrOptim(f=fn,theta=par,method="Nelder-Mead",ui=ui,ci=ci, ...)
@@ -30,7 +30,7 @@ if(visualize) {  # check ERROR on aarch64-apple-darwin20.4.0 (64-bit) (2021/05/1
 
 
 #true example
-library(GeneralizedHyperbolic)
+require("GeneralizedHyperbolic")
 args(dnig)
 
 

diff --git a/tests/t-fitdist-hessianpb.R b/tests/t-fitdist-hessianpb.R
@@ -1,4 +1,4 @@
-library(fitdistrplus)
+require("fitdistrplus")
 
 
 
@@ -27,7 +27,7 @@ vcov(fitdist(serving, "gamma", start=as.list(f1$estimate)))
 #an example with lower bounds for ztbinom
 if(FALSE)
 {
-  library(actuar)
+    require("actuar")
   n <- 1e3
   x <- rztbinom(n, 30, 1/2)
   lnl(c(35, 1/2), obs=x, dfun=dztbinom)

diff --git a/tests/t-fitdist-test-arguments.R b/tests/t-fitdist-test-arguments.R
@@ -1,4 +1,4 @@
-library(fitdistrplus)
+require("fitdistrplus")
 nbboot <- 100
 nbboot <- 10
 

diff --git a/tests/t-fitdist.R b/tests/t-fitdist.R
@@ -1,4 +1,4 @@
-library(fitdistrplus)
+require("fitdistrplus")
 nbboot <- 100
 nbboot <- 10
 
@@ -74,7 +74,7 @@ if(any(installed.packages()[,"Package"] == "rgenoud") && visualize)
   #wrap genoud function rgenoud package
   mygenoud <- function(fn, par, ...) 
   {
-    require(rgenoud)
+    require("rgenoud")
     res <- genoud(fn, starting.values=par, ...)        
     standardres <- c(res, convergence=0, counts=NULL)
 
@@ -93,7 +93,7 @@ if(any(installed.packages()[,"Package"] == "rgenoud") && visualize)
 #
 if(any(installed.packages()[,"Package"] == "actuar") && visualize)
 {
-  require(actuar)
+  require("actuar")
   #simulate a sample
   set.seed(1234)
   x4 <- rpareto(nsample, 6, 2)
@@ -206,7 +206,7 @@ quantile(fln, probs = 0.05)
 if(any(installed.packages()[,"Package"] == "mc2d") && visualize)
 {
   set.seed(1234)
-  require(mc2d)
+  require("mc2d")
   t <- rtriang(100,min=5,mode=6,max=10) # nsample not used : does not converge with a too small sample
   fCvM <- fitdist(t,"triang",method="mge",start = list(min=4, mode=6,max=9),gof="CvM")
   fKS <- fitdist(t,"triang",method="mge",start = list(min=4, mode=6,max=9),gof="KS")
@@ -251,7 +251,7 @@ if (FALSE) # NO INTEREST WITHOUT VISUALIZATION OF THE RESULT
 #
 #if(any(installed.packages()[,"Package"] == "gamlss.dist"))
 #{
-#    require(gamlss.dist)
+#    require("gamlss.dist")
 #    set.seed(1234)
 #    a=rexGAUS(100,mu=500,sigma=50,nu=75)
 #    fitdist(a,dexGAUS,start=list(mu=median(a),sigma=sqrt(var(a)/2),nu=sqrt(var(a)/2)))

diff --git a/tests/t-fitdistcens.R b/tests/t-fitdistcens.R
@@ -1,4 +1,4 @@
-library(fitdistrplus)
+require("fitdistrplus")
 
 nsample <- 500
 nsample <- 10
@@ -35,7 +35,7 @@ log10EC50 <-log10(fluazinam)
   #wrap genoud function rgenoud package
   mygenoud  <-  function(fn, par, ...) 
   {
-    require(rgenoud)
+    require("rgenoud")
     res  <-  genoud(fn, starting.values=par, ...)        
     standardres  <-  c(res, convergence=0)
 

diff --git a/tests/t-gen-max-spacing-estim.R b/tests/t-gen-max-spacing-estim.R
@@ -1,4 +1,4 @@
-library(fitdistrplus)
+require("fitdistrplus")
 
 set.seed(123)
 

diff --git a/tests/t-getparam.R b/tests/t-getparam.R
@@ -1,12 +1,9 @@
-library(fitdistrplus)
-
+require("fitdistrplus")
 
 computegetparam <- fitdistrplus:::computegetparam
 
-
 computegetparam(names(formals(dgamma)))
 computegetparam(names(formals(pgamma)))
 computegetparam(names(formals(qgamma)))
 
-
 computegetparam(names(formals(dnbinom)))
diff --git a/tests/t-gofstat.R b/tests/t-gofstat.R
@@ -1,5 +1,4 @@
-library(fitdistrplus)
-
+require("fitdistrplus")
 
 # (1) fit of two distributions by maximum likelihood estimation
 # to the serving size data

diff --git a/tests/t-init-actuar.R b/tests/t-init-actuar.R
@@ -1,15 +1,14 @@
 if(FALSE)
 {
 
-  require(fitdistrplus)
-
+  require("fitdistrplus")
 
   #test actuar initialization
 
   startargdefault <- fitdistrplus:::startargdefault
 
   #burr
-  library(actuar)
+  require("actuar")
   alpha <- 3
   x <- rburr(1000, alpha, 4, .1)