[Distr-commits] r1147 - branches/distr-2.7/pkg/distr/man

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Sun Jul 8 13:36:20 CEST 2018


Author: ruckdeschel
Date: 2018-07-08 13:36:18 +0200 (Sun, 08 Jul 2018)
New Revision: 1147

Modified:
   branches/distr-2.7/pkg/distr/man/0distr-package.Rd
   branches/distr-2.7/pkg/distr/man/AbscontDistribution-class.Rd
   branches/distr-2.7/pkg/distr/man/AbscontDistribution.Rd
   branches/distr-2.7/pkg/distr/man/Arcsine-class.Rd
   branches/distr-2.7/pkg/distr/man/Beta-class.Rd
   branches/distr-2.7/pkg/distr/man/Binom-class.Rd
   branches/distr-2.7/pkg/distr/man/Cauchy-class.Rd
   branches/distr-2.7/pkg/distr/man/Chisq-class.Rd
   branches/distr-2.7/pkg/distr/man/DExp-class.Rd
   branches/distr-2.7/pkg/distr/man/Dirac-class.Rd
   branches/distr-2.7/pkg/distr/man/DiscreteDistribution-class.Rd
   branches/distr-2.7/pkg/distr/man/Exp-class.Rd
   branches/distr-2.7/pkg/distr/man/Fd-class.Rd
   branches/distr-2.7/pkg/distr/man/Gammad-class.Rd
   branches/distr-2.7/pkg/distr/man/Geom-class.Rd
   branches/distr-2.7/pkg/distr/man/Hyper-class.Rd
   branches/distr-2.7/pkg/distr/man/LatticeDistribution-class.Rd
   branches/distr-2.7/pkg/distr/man/Lnorm-class.Rd
   branches/distr-2.7/pkg/distr/man/Logis-class.Rd
   branches/distr-2.7/pkg/distr/man/Nbinom-class.Rd
   branches/distr-2.7/pkg/distr/man/Norm-class.Rd
   branches/distr-2.7/pkg/distr/man/Pois-class.Rd
   branches/distr-2.7/pkg/distr/man/Td-class.Rd
   branches/distr-2.7/pkg/distr/man/Truncate-methods.Rd
   branches/distr-2.7/pkg/distr/man/Unif-class.Rd
   branches/distr-2.7/pkg/distr/man/UnivarLebDecDistribution-class.Rd
   branches/distr-2.7/pkg/distr/man/Weibull-class.Rd
   branches/distr-2.7/pkg/distr/man/internals.Rd
   branches/distr-2.7/pkg/distr/man/q-methods.Rd
Log:
[branches: distr]: began with major update to version 2.7 / mention problems with jupyter IRKernel and RStudio 

Modified: branches/distr-2.7/pkg/distr/man/0distr-package.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/0distr-package.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/0distr-package.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -33,6 +33,14 @@
 Note that, as usual, slots \code{d}, \code{p}, and \code{q} are vectorized
 in their first argument, but are not on the subsequent ones.
 
+In the environments of RStudio, see \url{https://www.rstudio.com/} and
+Jupyter IRKernel, see \url{https://github.com/IRkernel/IRkernel},
+calls to \code{q} are caught away from standard R evaluation and are treated
+in a non-standard way. This non-standard evaluation in particular throws
+errors at calls to our accessor methods \code{q} to slot \code{q} of the
+respective distribution object. To amend this, we provide function \code{q.l}
+as alias to our accessors \code{q}, so that our packages also become available
+ in these environments.
 
 Arithmetics and unary mathematical transformations for distributions are
 available: For \code{Distribution} objects \code{X} and \code{Y} expressions

Modified: branches/distr-2.7/pkg/distr/man/AbscontDistribution-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/AbscontDistribution-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/AbscontDistribution-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -169,6 +169,7 @@
 d(A3)(0) # The (approximated) density for x=0 is 0.43799.
 p(A3)(0) # The (approximated) probability that x <= 0 is 0.45620.
 q(A3)(.1) # The (approximated) 10 percent quantile is -1.06015.
+## in RStudio or Jupytier IRKernel, use q.l(.)(.) instead of q(.)(.)
 }
 \keyword{distribution}
 \concept{absolutely continuous distribution}

Modified: branches/distr-2.7/pkg/distr/man/AbscontDistribution.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/AbscontDistribution.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/AbscontDistribution.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -80,6 +80,7 @@
 +\tab +\tab -\tab +\tab p by \code{.Q2P}\cr
 +\tab -\tab +\tab +\tab d by \code{.P2D}\cr
 +\tab +\tab +\tab +\tab nothing\cr}
+
 For this purpose, one may alternatively give arguments \code{low1} and \code{up1} (\code{NULL} each by default,
 and determined through slot \code{q}, resp. \code{p}, resp. \code{d}, resp. \code{r} in this order
 according to availability),
@@ -88,6 +89,7 @@
 arguments \code{low} and \code{up} with default values \code{-Inf}, \code{Inf}, respectively.
 Of course all other slots may be specified as arguments.}
 
+
 \value{Object of class \code{"AbscontDistribution"}}
 
 

Modified: branches/distr-2.7/pkg/distr/man/Arcsine-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/Arcsine-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/Arcsine-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -67,6 +67,7 @@
 d(A)(c(-2,-1,-0.2,0,0.2,1,2)) # Density at x=c(-1,-0.2,0,0.2,1).
 p(A)(c(-2,-1,-0.2,0,0.2,1,2)) # cdf at q=c(-1,-0.2,0,0.2,1).
 q(A)(c(0,0.2,1,2)) # quantile function at at x=c(0,0.2,1).
+## in RStudio or Jupyter IRKernel, use q.l(A)(c(0,0.2,1,2)) instead
 }
 \keyword{distribution}
 \concept{absolutely continuous distribution}

Modified: branches/distr-2.7/pkg/distr/man/Beta-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/Beta-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/Beta-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -107,6 +107,7 @@
 # B0 is just the same beta distribution as Bn but with ncp = 0
 q(B0)(0.1) ## 
 q(Bn)(0.1) ## => from R 2.3.0 on ncp no longer ignored...
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 }
 \keyword{distribution}
 \concept{absolutely continuous distribution}

Modified: branches/distr-2.7/pkg/distr/man/Binom-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/Binom-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/Binom-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -96,6 +96,7 @@
 d(B)(1) # Density of this distribution is  0.5 for x=1.
 p(B)(0.4) # Probability that x<0.4 is 0.5.
 q(B)(.1) # x=0 is the smallest value x such that p(B)(x)>=0.1.
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 size(B) # size of this distribution is 1.
 size(B) <- 2 # size of this distribution is now 2.
 C <- Binom(prob = 0.5, size = 1) # C is a binomial distribution with prob=0.5 and size=1.

Modified: branches/distr-2.7/pkg/distr/man/Cauchy-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/Cauchy-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/Cauchy-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -90,6 +90,7 @@
 d(C)(1) # Density of this distribution is 0.3183099 for x=1.
 p(C)(1) # Probability that x<1 is 0.5.
 q(C)(.1) # Probability that x<-2.077684 is 0.1.
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 location(C) # location of this distribution is 1.
 location(C) <- 2 # location of this distribution is now 2.
 is(C,"Td") # no

Modified: branches/distr-2.7/pkg/distr/man/Chisq-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/Chisq-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/Chisq-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -107,6 +107,7 @@
 d(C)(1) # Density of this distribution is 0.2264666 for x = 1.
 p(C)(1) # Probability that x < 1 is 0.4772499.
 q(C)(.1) # Probability that x < 0.04270125 is 0.1.
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 df(C) # df of this distribution is 1.
 df(C) <- 2 # df of this distribution is now 2.
 is(C, "Gammad") # no

Modified: branches/distr-2.7/pkg/distr/man/DExp-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/DExp-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/DExp-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -82,6 +82,7 @@
 d(D)(1) # Density of this distribution is 0.1839397 for x = 1.
 p(D)(1) # Probability that x < 1 is 0.8160603.
 q(D)(.1) # Probability that x < -1.609438 is 0.1.
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 rate(D) # rate of this distribution is 1.
 rate(D) <- 2 # rate of this distribution is now 2.
 3*D ###  still a DExp -distribution

Modified: branches/distr-2.7/pkg/distr/man/Dirac-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/Dirac-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/Dirac-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -81,6 +81,7 @@
 d(D)(0) # Density of this distribution is 1 for x = 0.
 p(D)(1) # Probability that x < 1 is 1.
 q(D)(.1) # q(D)(x) is always 0 (= location).
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 location(D) # location of this distribution is 0.
 location(D) <- 2 # location of this distribution is now 2.
 }

Modified: branches/distr-2.7/pkg/distr/man/DiscreteDistribution-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/DiscreteDistribution-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/DiscreteDistribution-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -187,6 +187,7 @@
 q(D2)(pp)
 q(D2)(pp-1e-5)
 q(D2)(pp+1e-5)
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 q.r(D2)(pp)
 q.r(D2)(pp-1e-5)
 q.r(D2)(pp+1e-5)

Modified: branches/distr-2.7/pkg/distr/man/Exp-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/Exp-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/Exp-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -88,6 +88,7 @@
 d(E)(1) # Density of this distribution is 0.3678794 for x = 1.
 p(E)(1) # Probability that x < 1 is 0.6321206.
 q(E)(.1) # Probability that x < 0.1053605 is 0.1.
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 rate(E) # rate of this distribution is 1.
 rate(E) <- 2 # rate of this distribution is now 2.
 is(E, "Gammad") # yes

Modified: branches/distr-2.7/pkg/distr/man/Fd-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/Fd-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/Fd-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -91,6 +91,7 @@
 d(F)(1) # Density of this distribution is 0.1591549 for x=1 .
 p(F)(1) # Probability that x<1 is 0.5.
 q(F)(.1) # Probability that x<0.02508563 is 0.1.
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 df1(F) # df1 of this distribution is 1.
 df1(F) <- 2 # df1 of this distribution is now 2.
 Fn <- Fd(df1 = 1, df2 = 1, ncp = 0.5) 

Modified: branches/distr-2.7/pkg/distr/man/Gammad-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/Gammad-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/Gammad-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -86,6 +86,7 @@
 d(G)(1) # Density of this distribution is 0.3678794 for x=1.
 p(G)(1) # Probability that x<1 is 0.6321206.
 q(G)(.1) # Probability that x<0.1053605 is 0.1.
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 scale(G) # scale of this distribution is 1.
 scale(G) <- 2 # scale of this distribution is now 2.
 }

Modified: branches/distr-2.7/pkg/distr/man/Geom-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/Geom-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/Geom-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -94,6 +94,7 @@
 d(G)(1) # Density of this distribution is 0.25 for x = 1.
 p(G)(1) # Probability that x<1 is 0.75.
 q(G)(.1) # x = 0 is the smallest value x such that p(G)(x) >= 0.1.
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 prob(G) # prob of this distribution is 0.5.
 prob(G) <- 0.6 # prob of this distribution is now 0.6.
 as(G,"Nbinom")

Modified: branches/distr-2.7/pkg/distr/man/Hyper-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/Hyper-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/Hyper-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -84,6 +84,7 @@
 d(H)(1) # Density of this distribution is  0.45 for x=1.
 p(H)(1) # Probability that x<1 is 0.5.
 q(H)(.1) # x=1 is the smallest value x such that p(H)(x)>=0.1.
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 m(H) # m of this distribution is 3.
 m(H) <- 2 # m of this distribution is now 2.
 }

Modified: branches/distr-2.7/pkg/distr/man/LatticeDistribution-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/LatticeDistribution-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/LatticeDistribution-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -170,6 +170,7 @@
 d(D4)(1) # The (approximated) density for x=1 is 0.1282716.
 p(D4)(1) # The (approximated) probability that x<=1 is 0.1282716.
 q(D4)(.5) # The (approximated) 50 percent quantile is 3.
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 }
 \keyword{distribution}
 \concept{discrete distribution}

Modified: branches/distr-2.7/pkg/distr/man/Lnorm-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/Lnorm-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/Lnorm-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -91,6 +91,7 @@
 d(L)(1) # Density of this distribution is 0.2419707 for x=1.
 p(L)(1) # Probability that x<1 is 0.1586553.
 q(L)(.1) # Probability that x<0.754612 is 0.1.
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 meanlog(L) # meanlog of this distribution is 1.
 meanlog(L) <- 2 # meanlog of this distribution is now 2.
 }

Modified: branches/distr-2.7/pkg/distr/man/Logis-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/Logis-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/Logis-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -91,6 +91,7 @@
 d(L)(1) # Density of this distribution is 0.25 for x = 1.
 p(L)(1) # Probability that x < 1 is 0.5.
 q(L)(.1) # Probability that x < -1.197225 is 0.1.
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 location(L) # location of this distribution is 1.
 location(L) <- 2 # location of this distribution is now 2.
 }

Modified: branches/distr-2.7/pkg/distr/man/Nbinom-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/Nbinom-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/Nbinom-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -88,6 +88,7 @@
 d(N)(1) # Density of this distribution is  0.25 for x=1.
 p(N)(0.4) # Probability that x<0.4 is 0.5.
 q(N)(.1) # x=0 is the smallest value x such that p(B)(x)>=0.1.
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 size(N) # size of this distribution is 1.
 size(N) <- 2 # size of this distribution is now 2.
 }

Modified: branches/distr-2.7/pkg/distr/man/Norm-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/Norm-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/Norm-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -85,6 +85,7 @@
 d(N)(1) # Density of this distribution is  0.3989423 for x=1.
 p(N)(1) # Probability that x<1 is 0.5.
 q(N)(.1) # Probability that x<-0.2815516 is 0.1.
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 mean(N) # mean of this distribution is 1.
 sd(N) <- 2 # sd of this distribution is now 2.
 M <- Norm() # M is a normal distribution with mean=0 and sd=1.

Modified: branches/distr-2.7/pkg/distr/man/Pois-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/Pois-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/Pois-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -90,6 +90,7 @@
 d(P)(1) # Density of this distribution is 0.3678794 for x = 1.
 p(P)(0.4) # Probability that x < 0.4 is 0.3678794.
 q(P)(.1) # x = 0 is the smallest value x such that p(B)(x) >= 0.1.
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 lambda(P) # lambda of this distribution is 1.
 lambda(P) <- 2 # lambda of this distribution is now 2.
 R <- Pois(lambda = 3) # R is a Poisson distribution with lambda = 2.

Modified: branches/distr-2.7/pkg/distr/man/Td-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/Td-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/Td-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -106,6 +106,7 @@
 d(T)(1) # Density of this distribution is 0.1591549 for x = 1.
 p(T)(1) # Probability that x < 1 is 0.75.
 q(T)(.1) # Probability that x < -3.077684 is 0.1.
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 df(T) # df of this distribution is 1.
 df(T) <- 2 # df of this distribution is now 2.
 Tn <- Td(df = 1, ncp = 5) 

Modified: branches/distr-2.7/pkg/distr/man/Truncate-methods.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/Truncate-methods.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/Truncate-methods.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -36,7 +36,7 @@
 points lie on the same side of the median, we use this representation
 to enhance the range of applicability, in particular, for slot \code{r},
 we profit from Peter Dalgaard's clever log-tricks as indicated in 
-\url{http://article.gmane.org/gmane.comp.lang.r.general/126112}. To this
+\url{http://r.789695.n4.nabble.com/help-on-sampling-from-the-truncated-normal-gamma-distribution-on-the-far-end-probability-is-very-low-td868119.html#a868120}. To this
 end we use the internal functions
 (i.e.; non exported to namespace) \code{\link{.trunc.up}} and
 \code{\link{.trunc.low}} which provide functional slots \code{r,d,p,q} for 

Modified: branches/distr-2.7/pkg/distr/man/Unif-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/Unif-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/Unif-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -81,6 +81,7 @@
 d(U)(1) # Density of this distribution is 0.5 for x=1.
 p(U)(1) # Probability that x<1 is 0.5.
 q(U)(.1) # Probability that x<0.2 is 0.1.
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 Min(U) # Min of this distribution is 0.
 Min(U) <- 1 # Min of this distribution is now 1.
 Min(U) # Min of this distribution is 1.

Modified: branches/distr-2.7/pkg/distr/man/UnivarLebDecDistribution-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/UnivarLebDecDistribution-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/UnivarLebDecDistribution-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -265,6 +265,7 @@
 p(myLC)(0.3)
 r(myLC)(30)
 q(myLC)(0.9)
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 acPart(myLC)
 plot(myLC)
 d.discrete(myLC)(2)

Modified: branches/distr-2.7/pkg/distr/man/Weibull-class.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/Weibull-class.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/Weibull-class.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -90,6 +90,7 @@
 d(W)(1) # Density of this distribution is 0.3678794 for x=1.
 p(W)(1) # Probability that x<1 is 0.6321206.
 q(W)(.1) # Probability that x<0.1053605 is 0.1.
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 shape(W) # shape of this distribution is 1.
 shape(W) <- 2 # shape of this distribution is now 2.
 }

Modified: branches/distr-2.7/pkg/distr/man/internals.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/internals.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/internals.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -381,7 +381,7 @@
 classes \code{DiscreteDistribution} and \code{AbscontDistribution} for 
 one-sided truncation, using (for slot \code{r}) Peter Dalgaard's clever 
 log-tricks as indicated in 
-\url{http://article.gmane.org/gmane.comp.lang.r.general/126112}.
+\url{http://r.789695.n4.nabble.com/help-on-sampling-from-the-truncated-normal-gamma-distribution-on-the-far-end-probability-is-very-low-td868119.html#a868120}.
 
 \code{.modifyqgaps} modifies slot \code{q} for objects of class 
      \code{AbscontDistribution} in the presence of gaps, i.e.; if slot

Modified: branches/distr-2.7/pkg/distr/man/q-methods.Rd
===================================================================
--- branches/distr-2.7/pkg/distr/man/q-methods.Rd	2018-07-08 11:24:16 UTC (rev 1146)
+++ branches/distr-2.7/pkg/distr/man/q-methods.Rd	2018-07-08 11:36:18 UTC (rev 1147)
@@ -31,6 +31,7 @@
 require(distr)
 N <- Norm()
 q(N)(0.3)
+## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
 q.l(N)(0.3)
 }
 



More information about the Distr-commits mailing list