diff --git a/R/kfino.R b/R/kfino.R
index 0a20f777c18bd1c38e5c813f15fb2b1fee2e9bf9..5bed5dcf9fbc23d5cdaa3bb6b42c004ce4a43205 100644
--- a/R/kfino.R
+++ b/R/kfino.R
@@ -102,14 +102,6 @@
#' verbose=TRUE)
#' Sys.time() - t0
#'
-#' # --- With Optimization on initial parameters - EM method
-#' t0 <- Sys.time()
-#' resu1b<-kfino_fit(datain=spring1,
-#' Tvar="dateNum",Yvar="Poids",
-#' doOptim=TRUE,method="EM",param=param1,
-#' verbose=TRUE)
-#' Sys.time() - t0
-#'
#' # --- Without Optimization on initial parameters
#' t0 <- Sys.time()
#' param2<-list(m0=41,
@@ -129,26 +121,6 @@
#' doOptim=FALSE,
#' verbose=FALSE)
#' Sys.time() - t0
-#'
-#' # complex data on merinos2 dataset
-#' data(merinos2)
-#'
-#' t0 <- Sys.time()
-#' param3<-list(m0=NULL,
-#' mm=NULL,
-#' pp=NULL,
-#' aa=0.001,
-#' expertMin=10,
-#' expertMax=45,
-#' sigma2_m0=1,
-#' sigma2_mm=0.05,
-#' sigma2_pp=5,
-#' K=2,
-#' seqp=seq(0.5,0.7,0.1))
-#' resu3<-kfino_fit(datain=merinos2,
-#' Tvar="dateNum",Yvar="Poids",
-#' doOptim=TRUE,method="ML",param=param3)
-#' Sys.time() - t0
kfino_fit<-function(datain,Tvar,Yvar,
param=NULL,
doOptim=TRUE,method="ML",
diff --git a/R/utils_functions.R b/R/utils_functions.R
index 465eb6f2f94a847115c00f360a6bcb89c6a54f2a..2161bfbf41e9b273e02dea9289a304cae49b78ac 100644
--- a/R/utils_functions.R
+++ b/R/utils_functions.R
@@ -52,7 +52,8 @@ doutlier<-function(y,
#' Tvar can be expressed as a proportion of day in seconds
#' @param N numeric, length of the numeric vector of Y values
#'
-#' @details uses the same input parameter list than the main function
+#' @details utils_fit is a tool function used in the main \code{kfino_fit}
+#' function. It uses the same input parameter list than the main function.
#' @return a list
#' \describe{
#' \item{prediction}{vector, the prediction of weights}
@@ -250,7 +251,9 @@ utils_fit<-function(param,threshold,kappa=10,Y,Tps,N){
#' @param scalingC numeric, scaling constant. To be changed if the function is
#' not able to calculate the likelihood because the number of data is large
#'
-#' @details uses the same input parameter list than the main function
+#' @details utils_likelihood is a tool function used in the main
+#' \code{kfino_fit} function. It uses the same input parameter list than
+#' the main function.
#' @return a likelihood
#' @keywords internal
#' @export
@@ -401,7 +404,8 @@ utils_likelihood<-function(param,kappaOpt=7,Y,Tps,N,scalingC){
#' @param scalingC numeric, scaling constant. To be changed if the function is
#' not able to calculate the likelihood because the number of data is large
#'
-#' @details uses the same input parameter list than the main function
+#' @details utils_EM is a tool function used in the main \code{kfino_fit}
+#' function. It uses the same input parameter list than the main function.
#' @return a list:
#' \describe{
#' \item{m0}{numeric, optimized m0}
diff --git a/man/kfino_fit.Rd b/man/kfino_fit.Rd
index b0bc99d8230b1034e3773f8a77e5fbbbaae30c90..1f31a835b92fa5d74705c8c878bdcea2e62b4d71 100644
--- a/man/kfino_fit.Rd
+++ b/man/kfino_fit.Rd
@@ -132,14 +132,6 @@ resu1<-kfino_fit(datain=spring1,
verbose=TRUE)
Sys.time() - t0
-# --- With Optimization on initial parameters - EM method
-t0 <- Sys.time()
-resu1b<-kfino_fit(datain=spring1,
- Tvar="dateNum",Yvar="Poids",
- doOptim=TRUE,method="EM",param=param1,
- verbose=TRUE)
-Sys.time() - t0
-
# --- Without Optimization on initial parameters
t0 <- Sys.time()
param2<-list(m0=41,
@@ -159,24 +151,4 @@ resu2<-kfino_fit(datain=spring1,
doOptim=FALSE,
verbose=FALSE)
Sys.time() - t0
-
-# complex data on merinos2 dataset
-data(merinos2)
-
-t0 <- Sys.time()
-param3<-list(m0=NULL,
- mm=NULL,
- pp=NULL,
- aa=0.001,
- expertMin=10,
- expertMax=45,
- sigma2_m0=1,
- sigma2_mm=0.05,
- sigma2_pp=5,
- K=2,
- seqp=seq(0.5,0.7,0.1))
-resu3<-kfino_fit(datain=merinos2,
- Tvar="dateNum",Yvar="Poids",
- doOptim=TRUE,method="ML",param=param3)
-Sys.time() - t0
}
diff --git a/man/utils_EM.Rd b/man/utils_EM.Rd
index 7c19d22259f27bf9f0738e7d571fd83f7589b67f..e163b7bf4b0bd6fb67322d022bd4429a9b48e4f2 100644
--- a/man/utils_EM.Rd
+++ b/man/utils_EM.Rd
@@ -39,7 +39,8 @@ utils_EM a function to estimate the parameters `m_0` , `mm`, `pp` through
an Expectation-Maximization (EM) method
}
\details{
-uses the same input parameter list than the main function
+utils_EM is a tool function used in the main \code{kfino_fit}
+function. It uses the same input parameter list than the main function.
}
\examples{
set.seed(1234)
diff --git a/man/utils_fit.Rd b/man/utils_fit.Rd
index 4372b67d04c6af9fe4acec49ed7891fa804859f5..96acdcba02c564830010d6f925c0dfe535339669 100644
--- a/man/utils_fit.Rd
+++ b/man/utils_fit.Rd
@@ -40,7 +40,8 @@ utils_fit a fonction running the kfino algorithm to filter data and
detect outliers under the knowledge of all parameters
}
\details{
-uses the same input parameter list than the main function
+utils_fit is a tool function used in the main \code{kfino_fit}
+function. It uses the same input parameter list than the main function.
}
\examples{
set.seed(1234)
diff --git a/man/utils_likelihood.Rd b/man/utils_likelihood.Rd
index 05bf42e0a4b0df6d81d03ccff998ffba9e5dd182..596156993afb509b29cfa40c1ca7dac86c4cd1f1 100644
--- a/man/utils_likelihood.Rd
+++ b/man/utils_likelihood.Rd
@@ -33,7 +33,9 @@ utils_likelihood a function to calculate a likelihood on initial parameters
optimized by a grid search
}
\details{
-uses the same input parameter list than the main function
+utils_likelihood is a tool function used in the main
+\code{kfino_fit} function. It uses the same input parameter list than
+the main function.
}
\examples{
set.seed(1234)