https://github.com/cran/copBasic
Tip revision: f2424355e0b0746c78dda5eea66d6ec2cf74889a authored by William Asquith on 23 March 2020, 11:10:02 UTC
version 2.1.5
version 2.1.5
Tip revision: f242435
ChangeLog
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ChangeLog for R Package "copBasic" by W.H. Asquith
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Version 1.4--October 30, 2008 Initial Release (class project)
Version 1.5.0--August 31, 2011
1. Enhancement on derCOPinv.R when a solution is unbounded in uniroot()
to return NA as needed. This was discovered in massive simulation
from simcompositeCOP()---massive means 500k simulation counts.
2. Added Nelsen's copula in equation 4.2.12 as the N4212cop() function.
3. Removed and restructured the tabulated L-comoment solutions to the
Plackett-Plackett copula to clean up some loose ends and set up the
ability to load much much larger solutions sets that are too big
for CRAN distribution.
4. Major construction of the data subdirectory and changes to documentation.
Removed comp2lcomsPlackettPlackett.Rd, comp2lcomsPlackettPlackett2.Rd,
lcom2PLACKETTPLACKETTcop.R/Rd.
5. Added lcomoms2.cop2parameter.R/Rd (replaces lcom2PLACKETTPLACKETTcop.R/Rd).
6. Added data/PlackettPlackettNP.RData and man/PlackettPlackettNP.Rd.
7. Changes to the CITATION file.
8. Removed capitalization of arguments in the empricial quantile regression
(including f --> f.lowess): EMPIRqua.regress.R, EMPIRqua.regress2.R.
9. Removed capitalization of arguments in the median regression:
med.regressCOP(), med.regressCOP2(), and
qua.regressCOP(), qua.regressCOP2(), qua.regressCOP.draw()
10. Added level.setCOP() and level.setCOP2() that are dispatchers to special
features of level.curvesCOP() and level.curvesCOP2(), respectively. The
level curves functions required some extensive reorganization and
further error trapping to support the single level set return.
11. Added surfuncCOP() as the joint survival function. This function is
closely related to surCOP() but with subtle argument differences. This
new function included to be ever more consistent with Nelsen's book.
12. Added kmeasCOP() for the Kendall's Measure of a copula, which is critically
important for "secondary return period" computations.
13. Added alias of simCOPv() for simCOPmicro() to be in parallel with EMPIRsimv.
14. Relations between COP(), surCOP(), surfuncCOP(), duCOP(), and coCOP() are
illustrated in a script in inst/doc/CopulaRelations_BaseFigure_inR.txt
as a base figure and vector edited in inst/doc/CopulaRelationsFigure.pdf
Version 1.5.1--November 14, 2011
1. Added data/PlackettPlackettABKGtest.RData and
man/PlackettPlackettABKGtest.Rd.
2. Removed lcomoms2.cop2parameter.R/Rd.
3. Added lcomoms2.ABcop2parameter.R/Rd (replaces lcomoms2.cop2parameter.R/Rd).
4. Added lcomoms2.ABKGcop2parameter.R/Rd.
5. BUG FIX: Labeling inconsistency when sectionCOP() called with dercop=FALSE.
6. Added the EMPIRcop() function for estimation of the empirical copula.
7. Added the EMPIRcopdf() function to compute the entire data.frame() of
the empirical copula---the copula for each coordinate is computed.
8. Added the EMPIRgrid() function for computation of a regular grid of
the empirical copula---this grid will form the basis of other copula
operations on the empirical copula.
9. Added the EMPIRgridder() and EMPIRgridder2() functions for
computation of the sectional derivatives of the empirical copula from
EMPIRgrid().
10. Added the EMPIRgridderinv() and EMPIRgridderinv2() functions for
computation of the sectional derivatives of the empirical copula from
EMPIRgrid().
11. Added the EMPIRqua.regress() and EMPIRqua.regress2() functions for
quantile regression from grid emanating from EMPIRgridderinv() and
EMPIRgridderinv2().
12. Added the EMPIRmed.regress() and EMPIRmed.regress2() functions for
median regression from grid emanating from EMPIRgridderinv() and
EMPIRgridderinv2().
13. Added the EMPIRsim() function for simulation of V given U from the
empirical copula.
14. Added the EMPIRsimv() function for simulation of V given U (by
argument) from the empirical copula.
15. Documentation fixes in derCOP2.Rd, lcomoms2.ABcop2parameters.Rd,
lcomoms2.ABKGcop2parameter.Rd, PlackettPlackettNP.Rd, and
qua.regressCOP.Rd.
16. Enhanced error handling with COPinv(), COPinv2(), derCOPinv(), and
derCOPinv2().
17. Enhancement to derCOP() and derCOP2() by changing derivative direction
if near the 0 or 1 boundaries.
Version 1.5.2--July 30, 2012
1. med.regressCOP() and med.regressCOP() had arguments changed to match
the qua.regressCOP() and qua.regressCOP2() functions.
2. med.regressCOP.Rd and med.regressCOP2.Rd changed in argument to match
code.
3. qua.regressCOP(), qua.regressCOP2(), med.regressCOP(), and med.regressCOP2()
all now insert an NA in case a root solution could not be found.
4. Spelling corrections in DESCRIPTION: derivative and empirical.
Thanks CRAN team for the automated spell checkers.
Version 1.5.3--April 20, 2013
1. Added the ReineckeWells.RData and ReineckeWell266.RData.
** This version failed --timings checks by CRAN, never released **
Version 1.5.4--May 10, 2013
1. Prof. Ripley remarked that the DESCRIPTION of copBasic was too long.
This is a reasonably critique. The DESCRIPTION has been radically
shortened. The original (with new edits and organization) is now located
in the inst/doc/Extended_DESCRIPTION.txt file. WHA will use this file
as needed to provide further guidance into the package.
2. Contraction of --timings made to the following: tauCOP.Rd wolfCOP.Rd
level.curvesCOP.Rd med.regressCOP.Rd qua.regressCOP.Rd qua.regressCOP2.Rd.
Also some minor tweaks to the median and quantile regression examples
were made.
Version 1.6.0--September 26, 2014 (Quasi-closure to class project of 2008)
1. Added the Bernstein copula extension to EMPIRcop().
2. Changes to derCOP() and derCOP2() of accommodate vectorization yet still
retain the dynamic suspension of requested derivative direction should
need to be changed (overrided) [but only when needed]. Thus, tauCOP()
now does not kick off warnings.
3. Added isCOP.radsym() for a gridwise check on radial/reflection symmetry.
4. Added asCOP() to help build copulas with operational similarity to the
expected implementation style for the package.
5. Added isCOP.PQD() for testing postively quadrant dependency of a copula.
6. Added gridCOP() for supporting 3-D or 2-D image renderings of a copula.
7. Enchanced simCOP() for more speed and reporting features and vectorized
simCOPmicro().
8. Added the surfuncCOP() for the joint survival function of a copula, which
is subtly different from the survivial copula in surCOP.
9. Removed the ratcop argument from sectionCOP(). That feature is too much
like what isCOP.LTD() or isCOP.RTI() was already doing.
10. Comprehensive Rd auditing including the Examples and example expansion.
11. Removed the capital "F" for quantile regression level and replaced with
lower case "f" in qua.regress(), qua.regress2(), and updated all
examples. If I have broken code for a few users, I am sorry but the
refrain from capitals in function arguments should have been kept
consistent with version 1.5.0.
12. Added Hoeffding's Phi in hoefCOP().
13. Adjustments to the features of sectionCOP().
14. Enhanced indexing by suggestion of Amaranthe R. Biessen, whom also was
influential my major index extensions to the lmomco package.
15. Adjusted DESCRIPTION and NAMESPACE to only partially grab those few
functions needed from the lmomco package.
Version 1.7.0--January 3, 2015 (The "Joe 2014 Release" [many ideas from there])
1. Further refinement of documentation and continued work on highlighting
and extending the connections to numerical results of various kinds
reported in Nelsen (2006) as well as Joe (2014).
2. Extended hoefCOP() into Lp distances from independence and weaved in more
of Nelsen (2006).
3. Added LpCOP(), which is functionally the same as hoefCOP().
4. Minor documentation tweaks to EMPIRcop.Rd, EMPIRcopdf.Rd, EMPIRgrid.Rd,
PLACKETTpar.Rd, PlackettPlackettABKGtest.Rd, PlackettPlackettNP.Rd,
composite1COP.Rd, composite2COP.Rd, composite3COP.Rd,
isCOP.LTD.Rd, isCOP.RTI.Rd, isCOP.radsym.Rd,
lcomoms2.ABKGcop2parameter.Rd, and lcomoms2.ABcop2parameter.Rd.
5. Added extended example for isCOP* functions inside isCOP.radsym.Rd.
6. Added the Gumbel-Hougaard copula (GHcop) because WHA is studying the
method of L-comoments on this copula relative to the Plackett copula.
7. Fixed spelling of Roger Nelsen's last name in all Rd files (sorry Roger).
8. Added another example to copBasic-package.Rd.
9. Added FRECHETcop() and added utf-8 encoding to those Rd files requiring
the dicritic on Frechet: GHcop.Rd, M.Rd, PlackettPlackettABKGtest.Rd,
PlackettPlackettNP.Rd, and W.Rd.
10. Enhanced warning message in tauCOP() to point out that some failure of
numerical integration can be (often is?) attributable to singularity
for the given copula.
11. Added an example to PLACKETTpar.Rd that shows the development of a
polynomial for estimation of Kendall's Tau given Spearman's Rho of a
Plackett copula. Further, PLACKETTpar() now sets labels for the returned
theta using names().
12. Added additional discussion to isCOP.radsym.Rd to suggest that is seems
that radially symmetric copulas have zero L-comoments beyond
L-correlation. The literature seems silent on this question.
13. Improved a conditional on infinity in PLACKETTcop.R.
14. Added 'graphics' argument to simCOP.R to make is easier to turn off
graphical output from that function and also added the arguments 'snv',
'infsnv.rm', and 'trapinfsnv' as influence of Joe (2014) is incorporated.
15. Changed to more idiomatic R syntax in derCOPinv.R and derCOPinv2.R so that
the lines of code were reduced.
16. Added L-comoment example into the independence copula P.Rd.
17. Added diagCOPatf() for solution of the probabilities u and v that provide
joint probability F.
18. Added densityCOP() and densityCOPplot() following review of Joe (2014).
19. Added sample Blomqvist's Beta computation to blomCOP() after Joe (2014).
20. Added uvlmoms() and uvskewnewss() after Joe (2014).
21. Added lcomCOPpv() for simulating the sample distribution(s) of
L-correlation, L-coskew, and L-cokurtosis for a copula.
22. Added 'weibull' argument to EMPIRcop() [note the Joe (2014) often uses
Hazen plotting positions without so naming them as Hazen]
23. Added the Kullback-Leibler divergences, Jeffrey's divergence, and the
Kullback-Leibler sample size.
24. Added semicorCOP() for semicorrelations of a copula and(or) data.
25. Added isCOP.permsym() for a gridwise check on permutation symmetry.
26. Added vuongCOP() for Vuong's procedure of copula comparison along with an
extensive Note section showing the forefront of copBasic extension into
the inference problem.
Version 1.7.1--January 31, 2015
1. Minor changes to CITATION following CRAN email dated 01/09/2015.
Version 2.0.1--August 31, 2015
0. Some major documentation expansion here and there as cascading impacts from
the other changes listed below. Minor documentation formatting changes in
a select few Rd files and many proofreading passes through all documen-
tation resulted in modest additions and corrections. Overhaul of the
Examples sections to keep --timings down to < 0.01 elapsed seconds
for all documented functions outside \dontrun{} declarations on test
platform.
1. Added the "tol" argument to diagCOPatf and specified a tolerance tighter
than the default of uniroot because of apparent loss of precision
when experimenting with 1,000,000-year return periods.
2. Added a Note to GHcop.Rd showing analytical derivatives and the inverse.
3. Added jointCOP(), joint.curvesCOP(), joint.curvesCOP2() for an alternative
framework for computing joint probabilities with a feature of the two
conditions of AND and OR for the joint probability.
4. Typo correction in copBasic-package.Rd and extensions to that Rd considering
more about joint AND, joint OR, and mutually exclusive OR probabilities.
5. Added exp(log(...)) logic to PSP() for more accuracy for very small
probabilities to avoid division by small numbers.
6. Added in PSP.Rd discussion of PSP() returning NaN for zero probabilities.
7. Added (related to no. 5 and 6) trapped against a coupla NaN for zero
probabilities in root-solving in COPinv() and COPinv2(). The functions
jointCOP(), joint.curvesCOP(), joint.curvesCOP2() have this trap too.
7. Added Note section in duCOP.Rd about joint AND, OR, and exclusive OR.
8. Added reflection permutations to COP() and simCOPmicro() after Joe (2014) as
cited in documentation. WHA does not desire to implement the reflection
feature throughout the package---see the combined documentation of these
two functions.
9. Changed the named argument "swap" to "wrtV" in qua.regressCOP.draw to
parallel syntax of similar uses in copBasic.
10. Added inst/doc/CopulaRelationBaseFiginR.txt, which is an R script that
creates a base graphic suitable for manual vector editing defining
bivariate relations of probability a copulas.
11. Added Joe's Skewness of a copula by joeskewCOP() after Joe (2014) for
measurement of permutation asymmetry (skew).
12. Added "RhoE" of a bivariate extreme value copula by rhobevCOP() after
Joe (2014).
13. Added Kendall Function [kfuncCOP()/kmeasCOP()] along with very considerable
documentation concerning how they are presented in Nelsen (2006),
Salvadori et al. (2007), and Joe (2014). The inversion is kfuncCOPinv().
14. Added convexCOP() for a convex combination of two copulas after Joe (2014).
15. Removed the extensive copying of internal results within composite1COP(),
composite2COP(), and composite3COP()---should be big speed increase for
giant sample sizes.
16. Added Spearman's Footrule as footCOP() with sample estimation as well.
17. Added sample estimation to Gini Gamma in giniCOP(), Hoeffding Phi in
hoefCOP(), and Schweizer and Wolff Sigma in wolfCOP(), and for
parallelism---sample interface in rhoCOP() and tauCOP() to R's cor().
18. Added L-moments of the kfuncCOP() via kfuncCOPlmoms() and kfuncCOPlmom(),
which closely parallel theoretical L-moment computation using the
cdf2lmoms() and cdf2lmom() functions of the lmomco package.
19. Added Linear Spearman copula in FRECHETcop().
20. Added Asymmetric Gumbel-Hougaard extension to GHcop() with L-comoment demo.
21. Added prod2COP() for the *-product multiplication of copulas.
22. **DEPRECTATION ALERT** Added Hazen extension to EMPIRcop() and lumped
computation types into new argument "ctype"" and fully **removed**
the "weibull"" and "bernstein"" arguments.
23. Added GLcop() [Galambos] and HRcop() [Husler-Reiss] extreme value copulas.
24. **DEPRECTATION ALERT** Overhaul of kullCOP() into Monte Carlo integration
and deprecated numerical integration to kullCOPint(). Logic is simpler
at expense of longer computation times but does not suffer from
hard-to-mitigate divergent integral errors.
25. Added isfuncCOP() as a gridded numerical test on whether a bivariate
function appears to be a copula. Credit to user S. Kloibhofer for idea
and initial code---thanks for the support!
26. Added statTn() as a measure of a fitted coupla divergence from the
empirical copula.
27. Added the tail concentration function in tailconCOP().
28. Added the copBasic.fitpara.beta() in copBasic.fitpara as a potential
uni-dimensional or multi-dimensional parameter optimization interface.
This is not a maximum likelihood approach but matching of sample
statistics to theoretical (e.g. like a method of moments). Discussions
of maximum likelihood implementation with S. Kloibhofer are ongoing.
29. Overhaul of the output structure of vuongCOP() and added elements on the
return list to enhance clarity and added t-dist. for confidence interval.
Version 2.0.2--October 31, 2015
1. Added sobol argument to kullCOP() for Sobol sequences in the Monte Carlo
integration with an example in kullCOP.Rd. The package randtoolbox is
now imported from to get the sobol() function.
2. Added bilmoms() function to compute bivariate L-moments and remapping them
to L-comoments of L-correlation, L-coskew, and L-cokurtosis using
Monte Carlo integration and optional Sobol sequences.
3. Added the two-parameter Gumbel-Hougaard copula that is considered in the
paper providing the bivariate L-moments.
4. Added level to med.regress() and med.regressCOP2() for prediction interval
computation and added example to their use involving the Gaussian copula
from the copula package along with linear regression.
5. Migration of lcomCOPpv() from large sample simulation to Monte Carlo
integration for population estimate of L-comoments via the new bilmoms().
Version 2.0.3--May 31, 2016
1. Another deep rereading of the documentation and editorial revisions.
2. Extended the Gaussian copula example within med.regressCOP.Rd that deals
with the interaction with the copula package. (Reminder, WHA does not
want to just dump other copulas within copBasic. WHA wants just enough
directly implemented to show and validate core bivariate copula math-
ematical theory.)
3. Added the.zero and sumlogs to densityCOP() to facilitate maximum likelihood
estimation (see next item).
4. Added the.zero to vuongCOP() so it can dispatch that to densityCOP().
5. Added mleCOP() as an example of maximum likelihood estimation suitable for
the copBasic package but Examples extend into how the copula package
might be integrated to gain access to other copulas but still retain
a hosting within the copBasic package. Thanks to S. Kloibhofer for ideas.
6. Added rCOP() as a light-weight implementation of simCOP().
7. Extended use of the "tol" argument in taildepCOP() and tailconCOP() to
control the internally defined "resolution" variable.
8. Added psepolar() for pseudo-polar representation of bivariate data.
9. Added spectralmeas() for the spectral measure distribution of bivariate data
derived from the pseudo-polar representation.
10. Added StableTailDepFN() for the esimtation of the stable tail dependence
function and construction of level sets associated with it.
11. REMOVED: PlackettPlackettABKGtest.Rd, PlackettPlackettNP.Rd,
PlackettPlackettABKGtest.RData, PlackettPlackettNP.RData in
effort to reduce file size foot print of the package.
See lcomoms2.ABcop2parameterm() and lcomoms2.ABKGcop2parameter() to
explore how to prepopulate parameter to L-comoment mappings.
Version 2.0.4--June 3, 2016
1. Microchanges 2.0.3 to pass CRAN importation.
Version 2.0.5--February 24, 2017
1. Typo correction to DESCRIPTION and line ending changes to help hyphenation.
2. NAME CHANGE: StableTailDepFN() --> stabtaildepf()
3. Added importFrom("graphics", "mtext") for stabtaildepf() needs in NAMESPACE.
4. Small adjustments to throughout documentation, but more importantly, tried
running all examples + "dontrun" declarations + as well as the multitude
of "preformatted" code snippets. All seem to be working and several
errors and consistency issues have been resolved---so this exercise was
reasonably needed.
5. Error in blomCOP.Rd on old argument change: "sambeta" --> "as.sample".
6. NAME ADDITION: PLcop() and PLpar() are now available for Plackett copula.
7. Further auditing of kfuncCOP(), kfuncCOPinv(), and kfuncCOPlmoms(). Expanded
example of Kendall function L-moments.
Version 2.0.6--November 11, 2017
1. Added convexCOP() as a N-bivariate copula generalization of convex2COP().
2. Documentation adjustment to GHcop.Rd.
3. Added CLcop() for user R. Adat related to his own coding efforts.
Version 2.0.7--March 8, 2018
1. Clarified some documentation in bilmoms.Rd.
2. Expanded description in Examples in kullCOP.Rd.
Version 2.1.0--May 7, 2018
1. Minor Rd updates throughout.
2. Revision of warning() in wolfCOP().
3. Removed last of the repeated sequence computation inside nested sapply()s
with in EMPIRcop(), hoefCOP(), joeskewCOP(), and wolfCOP(). A test wtih
n=3000 for an as.sample=TRUE computation for wolfCOP() yielded about a
5-percent decrease in execution time. It is possible that some R idiom
exists for substantially more speed increase in situations of
"sapply(..., sapply(...))". However, investigations have not found one and
use of the "outer()" function does not appear applicable in testing because
of the lack of symmetry in the matrices involved.
4. Removed repeated sequence computation (though not nested) in kfuncCOP()
and vuongCOP(). This should be categorized as a "code cleaning" exercise.
5. Fixed error in vuongCOP.Rd about nonrejection of the Plackett with the wording
should be "rejection." Error was a result of poor cut and paste when first
written. It was the reverse Gumbel–Hougaard that was not rejected.
6. Fixed error in some accidentally swapped results in Examples of joeskewCOP.Rd.
7. BUG FIX: CLcop() was throwing an error when trying to estimate Kendall Tau and
the copula parameter from the observed data. The cor(, method="kendall")
function was being called and the estimate retrieved by $estimate as in
cor.test()$estimate.
8. Enhancement: Added some parsing of the ... to simCOP on which the delu and
derdir arguments are identified, used as needed, and then stripped before
the calls to plot() or points() to avoid "not a graphical parameter"
warnings. This has been an issue for nearly 10 years but finally WHA
sat down and figured out how to deal with it.
9. Enhancement: Added a sign test on the objective function in derCOPinv and
derCOPinv2. This will cut down on repeated warnings during simulations
when the calls to uniroot breakdown.
10. Added JOcopB5().
11. BUG FIX: rCOP() was not forwarding the sample size on down to simCOPmicro().
12. Added the contour.lwd argument to densityCOPplot().
13. BUG FIX: composite1COP() composite2COP() were not passing ... to COP().
This has not actually been a problem because most of the practical
applications of copula herein are not often called with other arguments.
However, composite3COP() was passing ... down to composite2COP().
14. Added FGMcop() for the Farlie-Gumbel-Morgenstern copula, which is actually
a recent (2012) generalization of this copula.
15. Added AMHcop() for the Ali-Mikhail-Haq copula.
16. Added alternative reflection arguments "1,2,3,4" to COP().
17. Added alias PAcop() for PARETOcop() to be parallel to the PLACKETTcop().
Version 2.1.1--December 1, 2018
1. Enhancement: Changed from sapply to u*v on return. This dates for a long
time back when the vectorization in R was not idiomatic for the author.
2. Added aicCOP(), bicCOP(), and rmseCOP(): a triad of similar goodness of fits.
3. Minor warning() editing in mleCOP.Rd when alerting user to use interval
search for one-parameter copulas.
4. Standardized all *.Rd files to utf8 encoding declaration whether needed or no.
Version 2.1.2--January 8, 2019
1. Added m=NA argument to aicCOP() and bicCOP() to pass the number of parameters
of the copula. Trivial to compute the number from standard copulas,
the problem is how to handle and count on the fly the number of parameters
for the various the compositing types.
2. Added warning of missing alpha or beta parameters in composite1COP and
composite2COP. Small speed it, but debugging when these are not given
(forgotten) becomes complicated. (See #3 and #4)
3. Added warning of missing kappa or gamma parameters in composite3COP.
(See #2 and #4)
4. Added warning of missing alpha in convex2COP() (See #2 and #3)
5. Enhancement: Added additional indexing for GHcop, GLcop, and HRcop as EV cops.
6. Added tEVcop() with implementation based on the Pickands dependence
function. Examples are provided. The tEVcop() is deemed useful because
of interest in semi-exhaustive EV-copula study with the easy addition of
a 2-parameter copula without triggering convex or compositing. However,
some literature indicates that the form itself with two parameters is
not really more expressive than the GHcop, GLcop, and HRcop.
7. Feature fix: COP.R had a weakness when parameters as a list are passed in
its handling of "cop" versus "cop1", "cop2" etc.
8. BUG FIX: Vectorization in convexCOP.R was not fully working for some
operations on composited copulas.
9. BUX FIX: isCOP.permsym() and isCOP.radsym() both had dispatching problems
when composited copulas were involved in "cop" being "matched by
multiple arguments" error in R. Had this always been a problem or had
R itself become more restricted? The fix was to insert a COP() call
as opposed cop() call (the argument named cop).
10. Added the Gaussian extreme-value copula as gEVcop().
11. Added rotation to cophalf (Nelsen's triangular copula) within the examples
of asCOP.Rd and bilmoms.Rd by including a para argument. This is useful
for further testing and as related to exploring nuskew() and nustar().
12. Overhauled joeskewCOP() after more extensive testing including nuskew() and
nustar() for parameter estimation. There are now changes in the numerical
outputs including the basic scale of each statistic. (See joeskewCOP.Rd)
The biggest problems seem to have been in the numerical version of the
sample nustar, which prompted the overhaul. *** No users have reported
any problems with the older scheme, but it needs to be stated that no
users are actually known to be using nuskew() and nustar(). ***
13. Added only.bilmoms argument to bilmoms() to skip L-comoment computation,
in order to speed execution.
14. Added lcomCOP() based on integrate(integrate()) nest for computation of the
bivariate L-moments and then conversion to the L-comoments. This is much
faster than bilmoms(). It is not remembered by the author why nested
integration was not originally implemented for bilmoms(). (Sorry.)
Testing indicates that lcomCOP() works well and is much much faster.
The function lcomCOPpv() will need revisition for a future release.
15. Added "1", "2", "3", "4" argument options for reflect in simCOPmicro() and
simCOPv() to be parallel with COP().
16. Made an editorial sweep throughout the documentation.
17. BUG FIX: semicorCOP() seems to have not had the truncation properly coded,
which was discovered during inspection of code as the Examples were
audited. However, the default truncation=0, would not show the problem.
Signs were not properly being used if truncation > 0 and matching logic
of Joe (2014, p. 73). Also argument 'samcor' renamed as 'as.sample' to
be consistent with other functions of the package.
18. Added the Raftery copula as RFcop.
19. GLcop() extended to a two-parameter version as a lower-extreme value
GL_LEV and related extension to another two-parameter version as the
"gamma-power mixture" of the Galambos. The two-parameter version does not
seem materially broader than the one-parameter Galambos (see Note).
The gamma-power mixture is though a different copula.
Version 2.1.3--July 1, 2019
1. Added documention in lcomCOP() stating that Chine and Benatia (2017) describe
trimmed L-comoments as the multivariate extensions of the univariate
trimmed L-moments. Unknown as to whether an extension jump should be made.
2. Added iterated Farlie-Gumbel-Morgenstern copula as FGMrcop(), which is not any more
useful than the existing generalization, but Chine and Benatia (2017) concern
themselves with the iterated FGM.
3. Documentation audit again with tiny changes to many Rds.
4. Added glueCOP() as another means of constructing other copulas.
5. BUG FIX: EMPIRqua.regress() and EMPIRqua.regress2() with lowess=TRUE could return
probabilities outside of [0,1]. Truncation to zero and unity is now made.
6. Warning Fix: EMPIRgridderinv()/EMPIRgridderinv2() in their calls to approx() could
trigger warnings about ties and deletion of them. We know therein that the
x values are ordered, so a switch was made to use ties="ordered" in approx().
Also, "F" was being used as the nonexceedance probability but R syntax
highlighting treats as FALSE, so switch made to FF. By association, the
EMPIRqua.regress()/EMPIRqua.regress2() also need the ties="ordered" in their
use of the approx() on the inversion of the gridded derivative of the empirical
copula.
7. Added an as.list() check to the empirical grid argument in both pairs of
EMPIRgridder()/EMPIRgridder2() and EMPIRgridderinv()/EMPIRgridderinv2().
8. BUG FIX: Through an audit of EMPIRcop.Rd examples, which then found that the
Bernstein argument to pass through lower-level dispatch to level.curvesCOP()
did not work. The ability for the para argument in EMPIRcop() now properly
supports the ability to trigger ctype and the bernstein arguments through
list embedment.
9. COP.Rd, diagCOPatf.Rd, and med.regressCOP.Rd examples edited to avoid using F with
change to FF as a variable for nonexceedance probability (see no. 6).
Version 2.1.4--July 2, 2019
1. Fixups in FGMcop.Rd (bad URL), HRcop.Rd (no encoding switch in the concept/keyword),
lcomCOP.Rd (bad URL), rhobevCOP.Rd (no commas in indexing or concepts) for
release to CRAN.
Version 2.1.5--03/22/2020
1. Extended RFcop() with a fit argument to toggle between Spearman Rho or Kendall Tau.
2. Extended COP.Rd with a example of taking a copula, such as the RFcop, that only has
positive association and reflecting it three different times to form alternative
association structures, including negative association, that its formula can not
natively attain.
3. Audit of AMHcop.Rd found documentation problems in the formula for Spearman's Rho.
Modified it and AMHcop() to show and respectively use the infinite series of
Machler (2014). Added the support for rho argument along with a fit argument
like RFcop() (see 2.1.5:1). Examples in AMHcop.Rd changed.
4. Audit pass of much of the documentation.
5. Changed a few Examples to dontruns because of the maturity of the package. The
--timings of the R CMD check were consulted. Should be a savings of less than
one second overall, but trying to help the CRAN.
6. gEVcop.Rd received a minor fix in the Examples.
7. Advancement: EMPIRgrid() was not passing ... to EMPIRcop().
8. Extended EMPIRgridderinv() and EMPIRgridderinv2() to accept a precomputed gridded
derivative in the dergrid argument.
9. Extended EMPIRgridder() and EMPIRgridder2() to throw a warning about NaN along
a row or column
warning("found nonfinite values on row|column=",i," in grid derivative")
The author has encountered one data set that produces NaN on two rows and
trying to understand how and why this is happening.
10. Extended the EMPIRcop() with a checker-board empirical copula, which is a type
of light smooth and adapted from the copula package.
11. Added a trap in EMPIRgridderinv() and EMPIRgridderinv2() if Kumaraswamy is set
and the Kumaraswamy fit fails, the original approx() to the inversion is
set for the failure and a warning() triggered as to which index was involved.
12. BUG FIX: An example within EMPIRsim.Rd need fixing and other minor cleanup.
13. Minor spelling checks during Rd auditing for margin protrusion on Rd2pdf.
POTENTIAL TODOs:
Continued inspection of the approx() use and whether ties="ordered" can be used
(see Version 2.1.3#6), it appears in all other cases that yes, we can move
to the ties="ordered" because the inversion of the gridded derivative of the empirical
copula is being used and structurally the "x" part of the approx will be ordered.
R/EMPIRsim.R: v <- approx(cols, y=v.available, xout=t, rule=2)$y
R/EMPIRsim.R: v1 <- approx(cols, y=v.available1, xout=t, rule=2)$y
R/EMPIRsim.R: v2 <- approx(cols, y=v.available2, xout=t, rule=2)$y
R/EMPIRsimv.R: v <- approx(cols, y=v.available, xout=t, rule=2)$y
R/EMPIRsimv.R: v1 <- approx(cols, y=v.available1, xout=t, rule=2)$y
R/EMPIRsimv.R: v2 <- approx(cols, y=v.available2, xout=t, rule=2)$y
R/kfuncCOP.R: empkc <- approx(c(0,FKin,1), c(0,Zin,1), xout=z)$y
lcomCOPpv() <--> vuongCOP() work as now lcomCOP() is available.
lcomCOPpv() might need some reworking too.
If two-parameter Galambos (Joe, 2014, p. 198) is not materially broader than
the one-parameter, does this hold for a two-parameter Gumbel hinted by
Joe (2014, p. 199)? Further investigation is needed.
Note: Joe's 2-p GHcop does appear different from Brahimi et. al (2015) version
of a 2-p GHcop. Should support for both be made? Are both the same? (Quick testing suggests that perhaps they are not, but mathematical checking has not been made [01/09/2019]).
Add the trimmed L-comoments?
\author{William Asquith \email{william.asquith@ttu.edu} }
Make such conversions throughout or go back to W.H. Asquith?
EMPIRcopdf() can be replaced by EMPIRcop() as the later is fully
vectorized itself and makes presumably a lesser impact on memory (faster)?
stabtaildepf.Rd --- Need to audit stabtaildepf.Rd and complete documentation.
Beirlant, J., Escobar-Bach, M., Goegebeur, Y., Guillou, A.: Bias-corrected estimation of stable tail dependence function. J. Multivar. Anal. 143, 453–466 (2016)
https://doi.org/10.1016/j.jmva.2015.10.006
Kiriliouk, A., Segers, J. & Tafakori, L. Extremes (2018) 21: 581.
https://doi.org/10.1007/s10687-018-0315-y
Implementation of state-of-the-practice nonparametric estimators of
lower and upper tail dependence parameters. Neither of the three books
cited within deal with this. A turn towards recommended literature by
Joe (2014) is needed.
Goodness-of-fit of the Kendall Function following Genest et. al. (2006,
Goodness-of-fit procedures for copula models based on the probability
integral transformation: Scand J. Statist 33.
Convergence evaluators for the Monte Carlo integration in bilmoms() and
kullCOP() to enhance computation times.
rhobevCOP() study for a copula yielding 0.
