Some doc updates

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: durmod
 Type: Package
 Title: Mixed Proportional Hazard Competing Risk Model
-Version: 1.1-1
-Date: 2019-07-24
+Version: 1.1-2
+Date: 2019-08-21
 Authors@R: person("Simen", "Gaure", email="[email protected]", role=c("aut","cre"), 
         comment=c(ORCID="https://orcid.org/0000-0001-7251-8747"))
 URL: https://github.com/sgaure/durmod

R/durmod-package.R

@@ -1,5 +1,6 @@
 #' A package for estimating a mixed proportional hazard competing risk model with the NPMLE.
 #'
+#' 
 #' The main method of the package is \code{\link{mphcrm}}. It has an interface
 #' somewhat similar to \code{\link{lm}}.  There is an example of use in \code{\link{datagen}}, with
 #' a generated dataset similiar to the ones in \cite{Gaure et al. (2007)}. For those who have
@@ -21,7 +22,7 @@
 #' may bias the estimates, not just increase uncertainty.  To account for unobserved heterogeneity, a
 #' random intercept is introduced, so that the hazards are of the form \eqn{h_i^j(\mu_k) = exp(X_i \beta_j + \mu_k)}
 #' for \eqn{k} between 1 and some \eqn{n}. The intercept may of course be written multiplicatively as
-#' \eqn{exp(X_i \beta_j) exp(\mu_k)}, that's why they are called \emph{proportional} hazards.
+#' \eqn{exp(X_i \beta_j) exp(\mu_k)}, that is why they are called \emph{proportional} hazards.
 #' 
 #' The individual likelihood depends on the intercept, i.e. \eqn{L_i(\mu_k)}, but we integrate it out
 #' so that the individual likelihood becomes \eqn{\sum p_k L_i(\mu_k)}. The resulting mixture
@@ -30,7 +31,7 @@
 #' Besides the function \code{\link{mphcrm}} which does the actual estimation, there are functions for
 #' extracting the estimated mixture, they are \code{\link{mphdist}}, \code{\link{mphmoments}} and a few more.
 #'
-#' There's a summary function for the fitted model, and there is a data set available with \code{data(durdata}} which
+#' There's a summary function for the fitted model, and there is a data set available with \code{data(durdata)} which
 #' is used for demonstration purposes. Also, an already fitted model is available there, as \code{\link{fit}}.
 #' 
 #' The package may use more than one cpu, the default is taken from \code{getOption("durmod.threads")}

inst/NEWS.Rd

@@ -1,5 +1,13 @@
 \name{NEWS}
 \title{durmod news}
+\section{Changes in version 1.1-2}{
+  \itemize{
+    \item Some adjustments to default parameters.
+    \item Use median, not mean, for the interval search for new
+    points. Use Neumaier compensated addition in computation of gradients.
+    \item Some more documentation.
+  }
+}
 \section{Changes in version 1.1-1}{
   \itemize{
     \item Fixed a bug in the interval censored gradient which slowed down

tests/sometests.Rout.save

@@ -1,5 +1,5 @@
 
-R Under development (unstable) (2019-07-05 r76784) -- "Unsuffered Consequences"
+R Under development (unstable) (2019-08-21 r77049) -- "Unsuffered Consequences"
 Copyright (C) 2019 The R Foundation for Statistical Computing
 Platform: x86_64-pc-linux-gnu (64-bit)
 
@@ -93,7 +93,7 @@ $coefs
 job.x1           0.89634 0.00931   96.2537  0.00e+00
 job.x2          -0.80995 0.00759 -106.7509  0.00e+00
 job.alpha       -0.17688 0.02670   -6.6241  3.67e-11
-job.f.2          0.07449 0.04287    1.7376  8.23e-02
+job.f.2          0.07449 0.04287    1.7377  8.23e-02
 job.f.3         -0.06195 0.04409   -1.4049  1.60e-01
 job.f.4          0.11317 0.04148    2.7287  6.37e-03
 job.f.5          0.01854 0.04311    0.4301  6.67e-01
@@ -103,15 +103,15 @@ program.x2       0.37743 0.01749   21.5830 4.31e-101
 program.f.2      0.20536 0.13447    1.5271  1.27e-01
 program.f.3      0.02068 0.13735    0.1505  8.80e-01
 program.f.4      0.00632 0.12036    0.0525  9.58e-01
-program.f.5     -0.13482 0.14185   -0.9504  3.42e-01
+program.f.5     -0.13482 0.14185   -0.9505  3.42e-01
 program.f.6      0.28122 0.14694    1.9138  5.57e-02
 program.g.2      0.03025 0.13082    0.2312  8.17e-01
 program.g.3      0.14083 0.13864    1.0157  3.10e-01
 program.g.4     -0.02071 0.14072   -0.1472  8.83e-01
 program.f:g.2:2 -0.30106 0.19641   -1.5328  1.25e-01
 program.f:g.2:3 -0.24366 0.19296   -1.2627  2.07e-01
 program.f:g.2:4  0.03646 0.20306    0.1796  8.58e-01
-program.f:g.3:2  0.10878 0.19535    0.5569  5.78e-01
+program.f:g.3:2  0.10878 0.19535    0.5568  5.78e-01
 program.f:g.3:3 -0.17411 0.19189   -0.9073  3.64e-01
 program.f:g.3:4  0.16215 0.19720    0.8223  4.11e-01
 program.f:g.4:2 -0.00186 0.17351   -0.0107  9.91e-01
@@ -174,4 +174,4 @@ job 0.0172
 > 
 > proc.time()
    user  system elapsed 
- 11.809   0.231   4.793 
+   6.87    0.24    4.31