(math/R-survey) Updated 4.1.1 to 4.2.1

Following lines from inst/NEWS

4.2	Handling of influence functions has CHANGED. A function that supplies influence
	functions must supply one for every observation it was given in its input:
	use 0 for observations removed by subsetting. (for Guilherme Jacob)

	regTermTest(method="LRT") required the two models to use the same observations
	(of course), but didn't check, so IT WAS WRONG.
	It now subsets properly. (for Keiran Shao)

	This will probably be the *last* interpreted-R-only version of survey. Future
	versions will likely incorporate C++ code for faster variance computation and
	for small-area estimation.

	deffs in svyglm.svyrep.design (Ben Schneider)

	svynls() allows for prior (eg precision) weights (for Gary Nelson)

	improved names in svyquantile.svyrep.design (Ben Schneider)

	trimWeights() could get into an infinite recursion (Ingmar Sturm)

	data(myco) from Rao, Scott, and Skinner (originally from Clayton & Hills)

	as.svrepdesign now throws an error with post-stratified/raked/calibrated
	designs -- create replicates *first*, then calibrate (for Lauren Kennedy)

	trimWeights now works with replicate-weights designs

	score tests for svyglm (with Keiran Shao)

	svyby(), and thus svyboxplot(), didn't handle the new quantile functions
	correctly when standard error/ci weren't requested (Stephanie Zimmer, Raymond Pan)

	svycontrast() threw an error on the output of svyby() with return.replicates=TRUE
	(Alena Stern)

	Fix regTermTest for svycoxph for the methods lookup changes in R 4.0
	(and consequential change to marginpred)

	We don't provide model.matrix.svycoxph any more;use the inherited
	survival:::model.matrix.coxph

	Recent survival::coxph() switches to robust variances with non-integer weights
	so check for model$naive.var before model$var

	Disable the pass-through from predict.svycoxph to predict.coxph for type="expected"
	(Bryan Shepherd)

	svyby( svyvar) would throw an error on domains with only one observation
	(for Dirk Schumacher)

	svyvar() computes sample size 'n' in the same way for na.rm=TRUE as for a domain
	(for Raymond Pan)

	xdesign() for crossed designs (which aren't strictly surveys, but are basically similar)

	removed redundant loop in saddlepoint approximation to pchisqsum (Qiaolan Deng)

	fix in summary(svyivreg) for variances (Chandler McClellan)

	svyolr() didn't run for subsets of raked/calibrated designs (Antony Damico)

	add predict.svyolr (for Vincent Arel-Bundock)

	add anova.svycoxph (for Bryan Shepherd)

	add stringsToFactors=TRUE to svyby to ensure factors have same levels in domains
	(for various people including Stephanie Zimmer)

	more complicated svyby example in ?svycontrast

	svyranktest() gave an error for multiple groups with replicate weights (Kasuki Yoshida)

	Additional chisquared test for tables with zeros (CrossValidated question #571328)

	svydesign() has a 'calibrate.formula' option to tell R that your weights have
	already been calibrated/raked/post-stratified (for Tobias Schoch)

	svycontrast() didn't work on svrepglm objects without replicates (Thomas Loughlin)

	error in svycoxph with rescale=FALSE (Jing Zhang)

	error in vcov.svyrep.design with mse=TRUE (shows up in svyVGAM)

	svyquantile() didn't pay attention to interval_type for replicate weights (David Jorquera Petersen)

	svyquantile() qrules 5 to 9 now return the single data value when there's
	just one (David Jorquera Petersen)

	regTermTest() on svyolr() objects created in a function now finds the
	design object more reliably. (for Pedro Baldoni)

	regTermTest() will now test against null models in svycoxph()

	Fixes to svyquantile: https://github.com/bschneidr/r-forge-survey-mirror/pull/7
	(Ben Schneider)

	anova.svyloglin was broken by change to anova.glm(test=NULL)
	(Brian Ripley)

	One-sample svyttest() on logical variable now tests for P(TRUE==0) not P(FALSE==0)
	(Stephanie Zimmer)

	rename svykm.fit to svykm_fit because CRAN tests


(mef)