Fixd import warning with fGarch

DESCRIPTION

@@ -2,7 +2,7 @@ Type: Package
 Package: gratis
 Title: Generating Time Series with Diverse and Controllable
     Characteristics
-Version: 1.0.5
+Version: 1.0.7
 Authors@R: c(
     person("Yanfei", "Kang", , "[email protected]", role = "aut",
            comment = c(ORCID = "0000-0001-8769-6650")),

NAMESPACE

@@ -18,7 +18,6 @@ export(pi_coefficients)
 export(rmixnorm)
 export(rmixnorm_ts)
 export(simulate_target)
-import(fGarch)
 import(feasts)
 import(shiny)
 importFrom(GA,ga)
@@ -30,6 +29,8 @@ importFrom(doRNG,"%dorng%")
 importFrom(dplyr,bind_cols)
 importFrom(dplyr,mutate)
 importFrom(dplyr,select)
+importFrom(fGarch,garchSim)
+importFrom(fGarch,garchSpec)
 importFrom(foreach,"%do%")
 importFrom(foreach,"%dopar%")
 importFrom(foreach,foreach)

NEWS.md

@@ -1,3 +1,7 @@
+# gratis 1.0.7
+
+* Fixed dependency issue on CRAN.
+
 # gratis 1.0.5
 
 * Fixed the 'docType' issue.
@@ -20,7 +24,7 @@
 
 ## Improvements
 
-* Added new parameter 'output_format', give users an option to transform time series output data into a tsibble format.
+* Added new parameter `output_format`, giving users an option to transform time series output data into a `tsibble` format.
 * Update vignette content
 
 ## Bug fixes
@@ -33,4 +37,4 @@
 
 ## New features
 
-* The R package gratis (previously known as tsgeneration) provides efficient algorithms for generating time series with diverse and controllable characteristics.
+* The R package `gratis` (previously known as tsgeneration) provides efficient algorithms for generating time series with diverse and controllable characteristics.

R/gratis-package.R

@@ -23,7 +23,7 @@
 #' @importFrom GA startParallel garun
 #' @importFrom tsfeatures tsfeatures
 #' @importFrom doRNG "%dorng%"
-#' @import fGarch
+#' @importFrom fGarch garchSpec garchSim
 #' @import shiny
 #' @import feasts
 #' @keywords internal

R/rmixmorm.R

@@ -118,11 +118,11 @@ dmixnorm <- function(x, means, sigmas, weights, log = FALSE) {
 #' means.ar.par.list <- list(c(0, 0.8), c(0, 0.6, 0.3))
 #' require("fGarch")
 #' sigmas.spec <- list(
-#'   garchSpec(model = list(alpha = c(0.05, 0.06)), cond.dist = "norm"),
-#'   garchSpec(model = list(alpha = c(0.05, 0.05)), cond.dist = "norm")
+#'   fGarch::garchSpec(model = list(alpha = c(0.05, 0.06)), cond.dist = "norm"),
+#'   fGarch::garchSpec(model = list(alpha = c(0.05, 0.05)), cond.dist = "norm")
 #' )
 #' sigmas.list <- lapply(
-#'   lapply(sigmas.spec, garchSim, extended = TRUE, n = n),
+#'   lapply(sigmas.spec, fGarch::garchSim, extended = TRUE, n = n),
 #'   function(x) x$sigma
 #' )
 #' weights <- c(0.8, 0.2)
@@ -205,9 +205,9 @@ dmixnorm_ts <- function(y, means.ar.par.list, sigmas.list, weights, log = FALSE)
 ## means.ar.par.list = list(c(0, 0.8), c(0, 0.6, 0.3))
 
 ## require("fGarch")
-## sigmas.spec <- list(garchSpec(model = list(alpha = c(0.05, 0.06)), cond.dist = "norm"),
-##                     garchSpec(model = list(alpha = c(0.05, 0.05)), cond.dist = "norm"))
-## sigmas.list <- lapply(lapply(sigmas.spec, garchSim, extended = TRUE, n = n),
+## sigmas.spec <- list(fGarch::garchSpec(model = list(alpha = c(0.05, 0.06)), cond.dist = "norm"),
+##                     fGarch::garchSpec(model = list(alpha = c(0.05, 0.05)), cond.dist = "norm"))
+## sigmas.list <- lapply(lapply(sigmas.spec, fGarch::garchSim, extended = TRUE, n = n),
 ##                       function(x) x$sigma)
 ## weights <- c(0.8, 0.2)
 ## y = rmixnorm_ts(n = n, means.ar.par.list = means.ar.par.list, sigmas.list = sigmas.list,