version 5.95

DESCRIPTION

@@ -7,7 +7,7 @@ Description: Estimation and inference methods for models for conditional quantil
   risk are also now included. See Koenker, R. (2005) Quantile Regression, Cambridge U. Press,
   <doi:10.1017/CBO9780511754098> and Koenker, R. et al. (2017) Handbook of Quantile Regression, 
   CRC Press, <doi:10.1201/9781315120256>. 
-Version: 5.94
+Version: 5.95
 Authors@R: c(
     person("Roger", "Koenker",  role = c("cre","aut"), email =  "rkoenker@illinois.edu"),
     person("Stephen", "Portnoy",  role = c("ctb"), 
@@ -37,13 +37,12 @@ Maintainer: Roger Koenker <rkoenker@illinois.edu>
 Repository: CRAN
 Depends: R (>= 3.5), stats, SparseM
 Imports: methods, graphics, Matrix, MatrixModels, survival, MASS
-Suggests: tripack, interp, rgl, logspline, nor1mix, Formula, zoo,
-        R.rsp, conquer
+Suggests: interp, rgl, logspline, nor1mix, Formula, zoo, R.rsp, conquer
 License: GPL (>= 2)
 URL: https://www.r-project.org
 NeedsCompilation: yes
 VignetteBuilder: R.rsp
-Packaged: 2022-07-20 07:16:54 UTC; roger
+Packaged: 2023-04-08 15:56:50 UTC; roger
 Author: Roger Koenker [cre, aut],
   Stephen Portnoy [ctb] (Contributions to Censored QR code),
   Pin Tian Ng [ctb] (Contributions to Sparse QR code),
@@ -60,4 +59,4 @@ Author: Roger Koenker [cre, aut],
   Brian D Ripley [trl, ctb] (Initial (2001) R port from S (to my
     everlasting shame -- how could I have been so slow to adopt R!) and
     for numerous other suggestions and useful advice)
-Date/Publication: 2022-07-20 08:40:02 UTC
+Date/Publication: 2023-04-08 17:00:02 UTC

MD5

@@ -1,5 +1,5 @@
-78bca695accd7b0656a0cfba204ca71d *DESCRIPTION
-51bba033d741590ce4532c532b6f0ee6 *NAMESPACE
+09cdde837df492abbef9e3d173057ff6 *DESCRIPTION
+59ae171f84eb2be52ee904fe100b1291 *NAMESPACE
 6c1789eaa459e5175106e2eba12bdbb4 *R/ParetoTest.R
 708697bbfb4cbcf4664df9e26380bc66 *R/anova.R
 3f4b1aec96f0b43d0ba9d3be270d36d4 *R/boot.R
@@ -11,13 +11,13 @@ efb3424dc544ed9c6ddd522c167c496b *R/crq.R
 d2f509eb6977017d1b77faae7de97a7c *R/lprq.R
 74e57bf2387ac9e764dfc185bec65980 *R/nlrq.R
 23abbfdfe6ab274c1ebe89aaa4d825ef *R/qrisk.R
-7d893b27d5bef0575a35401652734425 *R/quantreg.R
-a515a2986f20dd86d8523a9d57a64658 *R/rqss.R
+3bf5158a9b5a4d1b34d4713b9d360f29 *R/quantreg.R
+a77c6ad37ae6093e30c9d639e27351f0 *R/rqss.R
 f7723bc3ed3a21afb5b60417ddc7baa0 *R/sfn.R
 522fc9d16e1ef995877eaaf3972eb29e *R/table.R
 11102c1b9076b53ebaac51cc79b90bfb *R/tools.R
 00f6440dcfd495483f57d543f4918de0 *README
-f0741a89f0900a92c2167fce9f41748e *build/vignette.rds
+e4f5a43500c17dc9259fb152401d9b32 *build/vignette.rds
 56ef7db1af717ba44a86062560b034df *data/Bosco.rda
 403622377f41685bab4f044f2dac7785 *data/CobarOre.rda
 3d69ca4dff26067565dddb340c8d12a3 *data/Mammals.rda
@@ -38,20 +38,20 @@ b4f9fd933511f97b0f7408dc6b401c4d *demo/Mel.R
 8871644563874ecaf6184266985d5e72 *demo/Polson.R
 f6b197c9dd0ccf97b10fab9e8f9be542 *demo/RB-r.R
 a9cc1e5271ab2c9f1311705ac34b0401 *demo/arqss.R
-bf129f55ee6496d79dc7ff9d222e6538 *demo/cobar.R
+fcf5e10320aea6e0ad0b4f949da834e1 *demo/cobar.R
 4288d49cb3eb56ec86798b28da27e791 *demo/combos.R
 f859ed7e3664566f9d74636d537b8762 *demo/cpoint.R
 6c55988db9dee0d6dbde385185967de2 *demo/crquis.R
 d907e0e11fd1a4007ca28a3d1b03efed *demo/engel1.R
 66c9a9b4a33a03bba9805d4b6dbd1cbb *demo/engel2.R
-883cddc238cc016226b9275eba20b0d1 *demo/hinged.R
+7ac73a95fd412129c2d1295a00d6865f *demo/hinged.R
 2b83cdb0cd34debfcd80ef266f07f0b4 *demo/panelfig.R
 ea9c96de3d670a1fa922585cf85789e3 *demo/predemo.R
 32f68b8e497d02b2cae7cf5f9b83ff52 *demo/rqsslasso.R
 5235d61a73c80e7eb83777d7d923d144 *demo/stack.R
 a582af0bad3d273cb076a346c906cba5 *demo/subset.R
-e33f35e40b1769692b44c92d22dbf446 *inst/ChangeLog
-f66010e65bd560dd445575e83da64ec5 *inst/FAQ
+ef52e0ad2328df7ff175e69eafb215f3 *inst/ChangeLog
+8266697d263517278ba9c7d5a97ef42a *inst/FAQ
 f2732c4ab5eb2f4ca3421239a030f0ee *inst/TODO
 3fb70411ec441d151dcae73d63a5e018 *inst/doc/crq.pdf
 48b99baf4f65ac9b9a820769d55a75f0 *inst/doc/crq.pdf.asis
@@ -94,16 +94,16 @@ d2e7a73053e94b9a0444af290d0a19a1 *man/nlrq.control.Rd
 01a0f1c6e3d5edb2ab5e8592b9d88620 *man/plot.KhmaladzeTest.Rd
 aa5102d7ad3c26a1eb17570d8e712134 *man/plot.rq.process.Rd
 f147921961ec856f8ab74dccc81466cc *man/plot.rqs.Rd
-4d2092b283422d94e7503feabadd5c5f *man/plot.rqss.Rd
+c13ffb80fa594fbfcecc2d2b1dbbf55a *man/plot.rqss.Rd
 ded41d155578d1d75df60ab5332c6fac *man/plot.summary.rqs.Rd
 db8b8073598318c738c5e475a8e74c62 *man/predict.rq.Rd
-9c25bb014134d8c1caa4c81d13fc4fea *man/predict.rqss.Rd
+ac427a32840e5aabddb87df2ff2b64a2 *man/predict.rqss.Rd
 4eeff49d40b43c732f92ab317d9b7650 *man/print.KhmaladzeTest.Rd
 686fc7e0c9f3138fd5ff01645b8e9911 *man/print.rq.Rd
 5745e185fe3d47339bd0242bdbc29e23 *man/print.summary.rq.Rd
 8d1f34ce14b8da44a7a84ce9eac0e099 *man/q489.Rd
 261f6c62bdd9db554c3d7999185f191c *man/qrisk.Rd
-680fa8e297ae6321ca1f509fc915e765 *man/qss.Rd
+e7fa217bf726ed0efa7342f4fb4d310b *man/qss.Rd
 a916d9f3d2bed1c77cba165f268873a6 *man/ranks.Rd
 e4a4292807cd1a251a98f57e7892e427 *man/rearrange.Rd
 6f68d1c8d2c8cc7009c9c13f102acd27 *man/residuals.nlrq.Rd
@@ -127,8 +127,8 @@ c42b5515ccf48527ae43449357b3dfb0 *man/rq.process.object.Rd
 0a8b72f28db402c6333d4387f0fca020 *man/rq.wfit.Rd
 7f71e0ab0e75719d478a54b4404f896d *man/rqProcess.Rd
 47b5d67bdd5108808d62c0905ab8e58a *man/rqs.fit.Rd
-fa661a6dca9dc2468b439ae701c5f636 *man/rqss.Rd
-89ff04eb1bbb0da28d2bb6a514af85f6 *man/rqss.object.Rd
+60adfb48bc8cf2d2728035eb0d19f547 *man/rqss.Rd
+1d5e4c75789a5fac11763df6b7edef03 *man/rqss.object.Rd
 7a198b2a81968dc5da8b7f59ff282714 *man/sfn.control.Rd
 2dfb6597245f45ee542f157105db4bc4 *man/srisk.Rd
 cf9fd105c0bd87edbcce9ec4a71780e5 *man/summary.crq.Rd

NAMESPACE

@@ -30,7 +30,7 @@ importFrom("stats", ".checkMFClasses", ".getXlevels", "AIC", "approx",
      "optim", "pchisq", "pf", "pnorm", "predict", "printCoefmat",
      "pt", "qnorm", "qt", "quantile", "reformulate", "relevel",
      "resid", "residuals", "rexp", "runif", "setNames", "start",
-     "stepfun", "supsmu", "terms", "uniroot", "var")
+     "stepfun", "supsmu", "terms", "uniroot", "var", "napredict")
 
 S3method(AIC, nlrq)
 S3method(AIC, rq)

R/quantreg.R

@@ -284,7 +284,7 @@ function (object, newdata, type = "none", interval = c("none",
     "confidence"), level = 0.95, na.action = na.pass, ...)
 {
     if (missing(newdata))
-        return(object$fitted)
+	return(napredict(object$na.action, object$fitted))
     else {
         tt <- terms(object)
         Terms <- delete.response(tt)
@@ -364,7 +364,8 @@ function (object, newdata, type = "none", interval = c("none",
 function (object, newdata, type = "Qhat", stepfun = FALSE, na.action = na.pass, ...)
 {
    ## with all defaults
-   if(missing(newdata) && !stepfun && (type == "Qhat")) return(object$fitted)
+   if(missing(newdata) && !stepfun && (type == "Qhat")) 
+       return(napredict(object$na.action, object$fitted))
 
    ## otherwise
    tt <- delete.response(terms(object))
@@ -418,7 +419,8 @@ function (object, newdata, type = "Qhat", stepfun = FALSE, na.action = na.pass,
 "predict.rq.process" <-
 function (object, newdata, type = "Qhat", stepfun = FALSE, na.action = na.pass, ...)
 {
-    if(missing(newdata) && !stepfun && (type == "Qhat")) return(object$fitted)
+    if(missing(newdata) && !stepfun && (type == "Qhat")) 
+	return(napredict(object$na.action, object$fitted))
     tt <- terms(object)
     Terms <- delete.response(tt)
     m <- model.frame(Terms, newdata, na.action = na.action,