version 5.0

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: BayesGOF
 Type: Package
 Title: Bayesian Modeling via Goodness-of-Fit
-Version: 4.2
-Date: 2018-08-15
+Version: 5.0
+Date: 2018-10-02
 Author: Subhadeep Mukhopadhyay, Douglas Fletcher
 Maintainer: Doug Fletcher <tug25070@temple.edu>
 Description: A Bayesian data modeling scheme that performs four interconnected tasks: (i) characterizes the uncertainty of the elicited parametric prior; (ii) provides exploratory diagnostic for checking prior-data conflict; (iii) computes the final statistical prior density estimate; and (iv) executes macro- and micro-inference. Primary reference is Mukhopadhyay, S. and Fletcher, D. 2018 paper "Generalized Empirical Bayes via Frequentist Goodness of Fit" (<https://www.nature.com/articles/s41598-018-28130-5 >). 
@@ -11,6 +11,6 @@ Suggests: knitr, rmarkdown
 VignetteBuilder: knitr
 License: GPL-2
 NeedsCompilation: no
-Packaged: 2018-08-15 13:41:25 UTC; dougf
+Packaged: 2018-10-03 23:59:37 UTC; dougf
 Repository: CRAN
-Date/Publication: 2018-08-15 15:10:03 UTC
+Date/Publication: 2018-10-04 04:20:09 UTC

MD5

@@ -1,19 +1,21 @@
-ffeaebb8d7e4717f16ea9b2c41eb93aa *DESCRIPTION
-ec940df8b478e5daa81702578bb388ae *NAMESPACE
+d2b97fac75bd8aa392c42de214c35173 *DESCRIPTION
+52559619c64eec043eaaa899cecda3ca *NAMESPACE
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+12cb9a250b0071f90d7e19bf46613c8d *R/DS.entropy.R
 56dfac1f74749c934dbbe45b0a69ac49 *R/DS.macro.inf.R
 555db678e634782b3320744b6dacf11c *R/DS.macro.inf.bbu.R
 dd831259b8849db6456c5e947d519324 *R/DS.macro.inf.nnu.R
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 3653494e669368a0bf318488cb6a3983 *R/DS.macro.inf.pgu.R
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 770e76cc9f6abc3d5ab6054ff31f735d *R/DS.micro.inf.bbu.R
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-fdc1c724a49214d95fe44f63af35bc85 *R/DS.micro.inf.pge.R
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@@ -23,21 +25,23 @@ f95fb8a7a0b7deb760b9bcb9c9a5160b *R/DS.sampler.post.R
 f7b3ad32c70a318eab93a5e2d6e0bd85 *R/Reduce.LP.coef.univ.R
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 d4a2a8031c684b6364d3d6f442a7829e *R/gMLE.bb.R
-43e47e540af3ec33f977cd5475c20953 *R/gMLE.nn.R
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 fed21dfbc755bd9ed0a21ab9d33ff530 *R/gMLE.pg.R
 a231eceabe4c6921aad268cb9c0fa4fa *R/maxent.LP.par.R
 f5746d270cab6968f56a788f3db59fd7 *R/maxent.obj.convert.R
+f08a97ad543d7c464d114934cd586556 *R/plot.DS_FB_obj.R
 9a90c94d4dd49d22f7f7916c277874dc *R/plot.DS_GF.R
 346649ecfa05deedd2b97135bc609e0b *R/plot.DS_GF_macro_mean.R
 f1b86002893fff1f39cb54e83c902186 *R/plot.DS_GF_macro_mode.R
 cef07eb0c6cd10c281f5b987d8390d08 *R/plot.DS_GF_micro.R
+9aee686905a7dc3738f38f1f440f6972 *R/print.DS_FB_obj.R
 32731dab82fe5d939ab07f068eece6e5 *R/print.DS_GF.R
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 3761a595aa4959da50466638f0ae4144 *R/print.DS_GF_micro.R
 fd8df5d7338962f7e53c178832de3972 *R/rPPD.ds.R
 bcff739ac82f9217249a066142b3cba1 *R/weight.fun.univ.R
-0f85f791ccfb6eb7810bf9e1a2ce5875 *build/partial.rdb
+a67350f97dab560408f0345f0f538823 *build/partial.rdb
 fdc0c3b81464efa67ff2789177a3db3a *build/vignette.rds
 2235da02896248caee37a6bfd8f1675e *data/AutoIns.rda
 890414d6043ab45f0fc2d487c774eb93 *data/ChildIll.rda
@@ -52,23 +56,25 @@ e30a8fe86c5a0e2b9a4d8a5f3fe2f4ce *data/galaxy.rda
 b2cc985b167635ee9460b40031cb97b1 *data/tacks.rda
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 cc1812eb703a57cffe97326febc8574e *data/ulcer.rda
-44879d46035e6dda8971e95d765ab7de *inst/doc/vignette_BayesGOF.R
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+6a70bcd127ddd4c1ef70f856f43e95ed *inst/doc/vignette_BayesGOF.html
 c30e5b6c12cd7c5ea1e61447150c0a28 *man/AutoIns.Rd
-9803b0637bdb49d45aaa0b42a6b92bfb *man/BayesGOF-package.Rd
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 88e9ed138513646c3fa94f0b5b92fe04 *man/ChildIll.Rd
 9da9900d16025e6e5791a31e3b0347d0 *man/CorbBfly.Rd
-c4ecbf044af78ba83c558a33d5b0e066 *man/DS.macro.inf.Rd
-c898739a400d0445501360292983d283 *man/DS.micro.inf.Rd
-ec1c359172a351ec961583f6474e065b *man/DS.posterior.reduce.Rd
-af75ea6905054e1ce2d7e50732da9c0b *man/DS.prior.Rd
-519d71731994e726a2f8ca4126584974 *man/DS.sampler.Rd
+e5503a98402c7ec26fbe944e965605e2 *man/DS.Finite.Bayes.Rd
+9ad500f822639144d9c9e15ef3e860a9 *man/DS.entropy.Rd
+75095692390430026f761737f76999b2 *man/DS.macro.inf.Rd
+cac0496fb5fda3b44d16013ecc28f9d4 *man/DS.micro.inf.Rd
+0fe26e34baab43b75a0ef33b6a1368d5 *man/DS.posterior.reduce.Rd
+157a54d41700c7dfe23223f386aa5dba *man/DS.prior.Rd
+92f416ef32fd52b2c6d28891577b840c *man/DS.sampler.Rd
 c903db2e6ed7f20061762a4b3adb5a27 *man/NorbergIns.Rd
 871e183eafd071cf4980b9b94aaf23b8 *man/arsenic.Rd
-899358de9873fdce6b71f25b5c3653bd *man/gLP.basis.Rd
+8a04f55d16769a1b7bba33327ed61769 *man/gLP.basis.Rd
 8cbf9d570c207a6af39fc2d6a8655f9e *man/gMLE.bb.Rd
-46f6eeb14dc7474c81c31475f95058fa *man/gMLE.nn.Rd
+c7d22ad242a3db8164a31cc316374682 *man/gMLE.nn.Rd
 94817fcd314bb713cb1a1f19c4cf8d12 *man/gMLE.pg.Rd
 51c6fc4ad5bd40d572d255e7edaefc0a *man/galaxy.Rd
 05aa95928c93f8ab47d262394b21099f *man/rat.Rd
@@ -78,4 +84,4 @@ d5183d11ad3e8d96e6b0b31b049c1a52 *man/surg.Rd
 df49ea886daeb9f1020bd92c84b02fd7 *man/tacks.Rd
 f2d62106571a4dd2509fa692d4f5fc8f *man/terb.Rd
 3571b511674108bd7031dbfadb2c78d0 *man/ulcer.Rd
-5b98e15e3525ca3fdf92e7c2467ccd62 *vignettes/vignette_BayesGOF.Rmd
+5e3d3ae72affb9f5a2b0e079408ac310 *vignettes/vignette_BayesGOF.Rmd

NAMESPACE

@@ -13,4 +13,6 @@ S3method(print, DS_GF_micro)
 S3method(plot, DS_GF)
 S3method(plot, DS_GF_macro_mean)
 S3method(plot, DS_GF_macro_mode)
-S3method(plot, DS_GF_micro)
+S3method(plot, DS_GF_micro)
+S3method(print, DS_FB_obj)
+S3method(plot, DS_FB_obj)