[Yuima-commits] r763 - in pkg/yuima: . R
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Tue Nov 23 11:58:23 CET 2021
Author: kyuta
Date: 2021-11-23 11:58:23 +0100 (Tue, 23 Nov 2021)
New Revision: 763
Modified:
pkg/yuima/DESCRIPTION
pkg/yuima/NEWS
pkg/yuima/R/spectralcov.R
Log:
fixed a bug regarding the argument psd in lmm
Modified: pkg/yuima/DESCRIPTION
===================================================================
--- pkg/yuima/DESCRIPTION 2021-10-23 15:46:21 UTC (rev 762)
+++ pkg/yuima/DESCRIPTION 2021-11-23 10:58:23 UTC (rev 763)
@@ -1,7 +1,7 @@
Package: yuima
Type: Package
Title: The YUIMA Project Package for SDEs
-Version: 1.10.9
+Version: 1.10.10
Depends: R(>= 2.10.0), methods, zoo, stats4, utils, expm, cubature,
mvtnorm
Imports: Rcpp (>= 0.12.1), boot (>= 1.3-2), glassoFast, wavethresh,
Modified: pkg/yuima/NEWS
===================================================================
--- pkg/yuima/NEWS 2021-10-23 15:46:21 UTC (rev 762)
+++ pkg/yuima/NEWS 2021-11-23 10:58:23 UTC (rev 763)
@@ -76,4 +76,5 @@
2021/3/13: fixed a bug in qmle when joint = TRUE and the parameter space is one-dimensional
2021/3/15: fixed a bug in qmle when yuima at model@parameter at measure is character(0) and yuima at model@measure.type is "CP"
2021/8/16: fixed a bug in simulate when the jump intensity is not a parameter
-2021/9/24: fixed a bug regarding the "fixed" argument in qmle
\ No newline at end of file
+2021/9/24: fixed a bug regarding the "fixed" argument in qmle
+2021/11/23: fixed a bug regarding the "psd" argument in lmm
\ No newline at end of file
Modified: pkg/yuima/R/spectralcov.R
===================================================================
--- pkg/yuima/R/spectralcov.R 2021-10-23 15:46:21 UTC (rev 762)
+++ pkg/yuima/R/spectralcov.R 2021-11-23 10:58:23 UTC (rev 763)
@@ -198,9 +198,9 @@
inv.Ik <- 1/rowSums(Ijk)
if(psd){
+ cmat <- abs(sum(Ijk*inv.Ik*summand)/block)
+ }else{
cmat <- sum(Ijk*inv.Ik*summand)/block
- }else{
- cmat <- abs(sum(Ijk*inv.Ik*summand)/block)
}
result <- list(covmat = as.matrix(cmat), vcov = as.matrix(2 * mean(inv.Ik)/block), Sigma.p = Sigma.p)
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