version 1.4 2019-07-25
- Updated maintainer's email address.
version 1.3 2018-09-28
- Some surely useless 'as.double()' or 'as.integer()' were removed in all routines for faster results, a deeper check.
- Some interval checks in arguments, e.g. 'any(VecPk.s<=0|VecPk.s>1)' were replaced by 'min(VecPk.s)<=0|max(VecPk.s)>1' as the latter is almost 4 times faster. Below an example using the microbenchmark package:
> # Loading packages for comparison
> require(microbenchmark)
> require(ggplot2)
> x <- runif(n = 100000)
> y <- c(x,2)
> ans1 <- any(x<=0|x>1)
> ans2 <- min(x)<= 0|max(x)>1
> ans3 <- any(y<=0|y>1)
> ans4 <- min(y)<= 0|max(y)>1
> identical(ans1, ans2)
[1] TRUE
> identical(ans3, ans4)
[1] TRUE
> # Testing
> compare <- microbenchmark(any(x<=0|x>1), min(x)<= 0|max(x)>1, any(y<=0|y>1), min(y)<= 0|max(y)>1, times=10000)
> # Printing the comparison results
> print(compare)
Unit: microseconds
expr min lq mean median uq max neval
any(x <= 0 | x > 1) 708.761 722.513 898.3372 748.960 886.480 51354.474 10000
min(x) <= 0 | max(x) > 1 245.422 246.480 271.2233 251.064 299.373 5031.497 10000
any(y <= 0 | y > 1) 708.761 722.513 895.6946 745.434 886.127 50101.978 10000
min(y) <= 0 | max(y) > 1 245.422 246.832 270.3718 251.770 299.373 1034.933 10000
> # Plot of the comparison results
> autoplot(compare)
- Other arguments' checks that were using 'any()' were changed in a similar way for faster results.
version 1.2 2018-09-21
- A simple performance optimization is made in all routines, replacing 'any(is.na(x))' by 'anyNA(x)' for speed. Note that this needs R >= 3.1.0. See: https://stackoverflow.com/questions/6551825/fastest-way-to-detect-if-vector-has-at-least-1-na
- Some surely useless 'as.double()' or 'as.integer()' were removed in all routines.
version 1.1 2017-07-10
- There was a problem with the C code for the 'Pk.PropNorm.U()' function (in some cases the sum of the output vector did not match the sample size). It is now fixed.
- The CRAN check package submission NOTE: "Found no calls to: 'R_registerRoutines', 'R_useDynamicSymbols'" is now fixed.
- Some polishing of the user's manual.
version 1.0-2 2016-06-12
- Negative values of the MOS variable 'VecMOS.U' are converted to zero before when computing inclusion probabilities using the function 'Pk.PropNorm.U()'.
- Some polishing of the user's manual.
version 1.0-1 2016-01-02
- Two point estimators for the empirical cumulative distribution function were added.
- Some polishing of the user's manual.
version 0.9-9 2014-05-13
- Updated maintainer's email address.
version 0.9-8 2013-12-31
- Some linearisation variance estimators for the ratio point estimator are added.
- Restrictions on the input of n and N (sample and population sizes) are relaxed. It is no longer needed that they are (formally) integers. They now can be double-precision scalars with zero-valued fractional parts.
- When using the Tukey's Jackknife it is now optional to utilise a finite population correction (PFC). A logical argument that indicates whether to use it or not was added to those functions that implement Tukey's jackknife variance estimators.
- Some polishing of the user's manual.
version 0.9-7 2013-12-14
- A point estimator for the intercept regression coefficient is added.
- Some variance estimators for the intercept regression coefficient point estimator are added.
- Some polishing of the user's manual.
version 0.9-6 2013-09-03
- Updated references and some polishing of the user's manual.
- First ChangeLog entry.