Merge pull request #11 from nimble-dev/nMixture

Updated master to match CRAN release from 0.2.0

.Rbuildignore

@@ -7,3 +7,4 @@ run_tests\.R
 ^\.travis\.yml$
 ^doc$
 ^Meta$
+\.Rmd$

DESCRIPTION

@@ -1,14 +1,14 @@
 Package: nimbleEcology
 Type: Package
 Title: Distributions for Ecological Models in 'nimble'
-Version: 0.1.1
+Version: 0.2.0
 Maintainer: Benjamin R. Goldstein <[email protected]>
 Authors@R: c(person("Benjamin R.", "Goldstein", role = c("aut", "cre"),
                      email = "[email protected]"),
               person("Daniel", "Turek", role = "aut"),
               person("Lauren", "Ponisio", role = "aut"),
               person("Perry", "de Valpine", role = "aut"))
-Date: 2019-09-24
+Date: 2020-02-20
 Description: Common ecological distributions for 'nimble' models in the form of nimbleFunction objects. 
   Includes Cormack-Jolly-Seber, occupancy, dynamic occupancy, hidden Markov, and dynamic hidden Markov models.
   (Jolly (1965) <doi:10.2307/2333826>, Seber (1965) <10.2307/2333827>, Turek et al. (2016) <doi:10.1007/s10651-016-0353-z>).
@@ -19,11 +19,12 @@ Encoding: UTF-8
 LazyData: true
 URL: https://github.com/nimble-dev/nimbleEcology
 Collate:
-  dDynOcc.R
   dCJS.R
+  dDynOcc.R
   dDHMM.R
   dHMM.R
   dOcc.R
+  dNmixture.R
   zzz.R
 RoxygenNote: 6.1.1
 Suggests: 

NAMESPACE

@@ -20,6 +20,8 @@ export(dDynOcc_vvs)
 export(dDynOcc_vvv)
 export(dHMM)
 export(dHMMo)
+export(dNmixture_s)
+export(dNmixture_v)
 export(dOcc_s)
 export(dOcc_v)
 export(rCJS_ss)
@@ -42,9 +44,12 @@ export(rDynOcc_vvs)
 export(rDynOcc_vvv)
 export(rHMM)
 export(rHMMo)
+export(rNmixture_s)
+export(rNmixture_v)
 export(rOcc_s)
 export(rOcc_v)
 import(nimble)
 importFrom(stats,dbinom)
 importFrom(stats,rbinom)
 importFrom(stats,runif)
+importFrom("stats", "dpois", "qpois", "rpois")

R/dCJS.R

@@ -148,6 +148,8 @@ dCJS_ss <- nimbleFunction(
     if (len != 0) {
       if (len != length(x)) stop("Argument len must match length of data, or be 0.")
     }
+    if (x[1] != 1) stop("dCJS requires specifying first capture. x[1] must equal 1.")
+
     ## Note the calculations used here are actually in hidden Markov model form.
     probAliveGivenHistory <- 1
     ## logProbData will be the final answer
@@ -191,6 +193,7 @@ dCJS_sv <- nimbleFunction(
       if (len != length(x)) stop("Argument len must match length of data, or be 0.")
     }
     if (length(x) != length(probCapture)) stop("Length of probCapture does not match length of data.")
+    if (x[1] != 1) stop("dCJS requires specifying first capture. x[1] must equal 1.")
 
     ## Note the calculations used here are actually in hidden Markov model form.
     probAliveGivenHistory <- 1
@@ -238,6 +241,7 @@ dCJS_vs <- nimbleFunction(
     }
     if (length(probSurvive) < length(x) - 1)
       stop("Length of probSurvive must be at least length of data minus 1.")
+    if (x[1] != 1) stop("dCJS requires specifying first capture. x[1] must equal 1.")
 
     ## Note the calculations used here are actually in hidden Markov model form.
     probAliveGivenHistory <- 1
@@ -290,6 +294,8 @@ dCJS_vv <- nimbleFunction(
     if (length(probSurvive) < length(x) - 1)
       stop("Length of probSurvive must be at least length of data minus 1.")
     if (length(x) != length(probCapture)) stop("Length of probCapture does not match length of data.")
+    if (x[1] != 1) stop("dCJS requires specifying first capture. x[1] must equal 1.")
+
     ## Note the calculations used here are actually in hidden Markov model form.
     probAliveGivenHistory <- 1
     ## logProbData will be the final answer

R/dDHMM.R

@@ -1,7 +1,7 @@
-#' Dynamic Hidden Markov Model distribution for use in NIMBLE models
+#' Dynamic Hidden Markov Model distribution for use in \code{nimble} models
 #'
 #' \code{dDHMM} and \code{dDHMMo} provide Dynamic hidden Markov model
-#' distributions for NIMBLE models.
+#' distributions for \code{nimble} models.
 #'
 #' @name dDHMM
 #' @aliases dDHMM dDHMMo rDHMM rDHMMo
@@ -330,34 +330,3 @@ rDHMMo <- nimbleFunction(
 #     }
 #     return(ans)
 #   })
-
-
-
-registerDistributions(list(
-  dDHMM = list(
-    BUGSdist = "dDHMM(init, probObs, probTrans, len)",
-    Rdist = "dDHMM(init, probObs, probTrans, len)",
-    discrete = TRUE,
-    types = c('value = double(1)',
-              'init = double(1)',
-              'probObs = double(2)',
-              'probTrans = double(3)',
-              'len = double()'),
-    mixedSizes = TRUE,
-    pqAvail = FALSE))
-  )
-
-registerDistributions(list(
-  dDHMMo = list(
-    BUGSdist = "dDHMMo(init, probObs, probTrans, len)",
-    Rdist = "dDHMMo(init, probObs, probTrans, len)",
-    discrete = TRUE,
-    types = c('value = double(1)',
-              'init = double(1)',
-              'probObs = double(3)',
-              'probTrans = double(3)',
-              'len = double()'),
-    mixedSizes = TRUE,
-    pqAvail = FALSE))
-  )
-

R/dDynOcc.R

@@ -1,5 +1,5 @@
 # dDynOcc
-#' Dynamic occupancy distribution for use in NIMBLE models
+#' Dynamic occupancy distribution for use in \code{nimble} models
 #' \code{dDynOcc_**} and \code{rDynOcc_**} provide dynamic occupancy
 #' model distributions that can be used directly from R or in \code{nimble}
 #' models.

R/dHMM.R

@@ -1,4 +1,4 @@
-#' Hidden Markov Model distribution for use in NIMBLE models
+#' Hidden Markov Model distribution for use in \code{nimble} models
 #'
 #' \code{dHMM} and \code{dHMMo} provide hidden Markov model
 #' distributions that can be used directly from R or in \code{nimble}