Ajout des return() et update du namespace avec roxygen

NAMESPACE

@@ -1,24 +1,23 @@
-export(a.Crowder.Mod,
-a.Crowder,
-a.gauss,
-b.Crowder.Mod,
-b.Crowder,
-b.gauss,
-confidence.interval.QEE,
-covariance.QEE,
-eqn.Crowder.Mod,
-eqn.Crowder,
-eqn.gauss,
-gammaf.Crowder.Mod,
-gammaf.Crowder,
-M.Crowder.Mod,
-M.Crowder,
-M.gauss,
-obj.Crowder.Mod,
-obj.Crowder,
-obj.gauss,
-V.Crowder.Mod,
-V.Crowder,
-V.gauss,
-Wald.Test
-)
+export(M.Crowder)
+export(M.Crowder.Mod)
+export(M.gauss)
+export(V.Crowder)
+export(V.Crowder.Mod)
+export(V.gauss)
+export(Wald.Test)
+export(a.Crowder)
+export(a.Crowder.Mod)
+export(a.gauss)
+export(b.Crowder)
+export(b.Crowder.Mod)
+export(b.gauss)
+export(confidence.interval.QEE)
+export(covariance.QEE)
+export(eqn.Crowder)
+export(eqn.Crowder.Mod)
+export(eqn.gauss)
+export(gammaf.Crowder)
+export(gammaf.Crowder.Mod)
+export(obj.Crowder)
+export(obj.Crowder.Mod)
+export(obj.gauss)

R/M.Crowder.Mod.R

@@ -16,7 +16,7 @@
 #' @param dmean Derivative in respect to the parameter vector of the mean function of the distribution
 #' @param dsd Derivative in respect to the parameter vector of the standard deviation function of the distribution 
 #' @return M Matrix
-#' 
+#' @export M.Crowder.Mod
 #' @author Francois Pelletier
 M.Crowder.Mod <- function(param,Y,variancef,skewnessf,kurtosisf,dmean,dsd)
 {

R/M.Crowder.R

@@ -17,7 +17,7 @@
 #' @param dmean Derivative in respect to the parameter vector of the mean function of the distribution
 #' @param dsd Derivative in respect to the parameter vector of the standard deviation function of the distribution 
 #' @return M Matrix
-#' 
+#' @export M.Crowder
 #' @author Francois Pelletier
 M.Crowder <- function(param,Y,variancef,skewnessf,kurtosisf,dmean,dsd)
 {

R/M.gauss.R

@@ -13,7 +13,7 @@
 #' @param dmean Derivative in respect to the parameter vector of the mean function of the distribution
 #' @param dsd Derivative in respect to the parameter vector of the standard deviation function of the distribution
 #' @return M Matrix
-#' 
+#' @export M.gauss
 #' @author Francois Pelletier
 M.gauss <- function(param,Y,meanf,variancef,dmean,dsd)
 {

R/V.Crowder.Mod.R

@@ -13,7 +13,7 @@
 #' @param dmean Derivative in respect to the parameter vector of the mean function of the distribution
 #' @param dsd Derivative in respect to the parameter vector of the standard deviation function of the distribution 
 #' @return V Matrix
-#' 
+#' @export V.Crowder.Mod
 #' @author Francois Pelletier
 V.Crowder.Mod <- function(param,Y,variancef,dmean,dsd)
 {

R/V.Crowder.R

@@ -15,7 +15,7 @@
 #' @param dmean Derivative in respect to the parameter vector of the mean function of the distribution
 #' @param dsd Derivative in respect to the parameter vector of the standard deviation function of the distribution 
 #' @return V Matrix
-#' 
+#' @export V.Crowder
 #' @author Francois Pelletier
 V.Crowder <- function(param,Y,variancef,skewnessf,kurtosisf,dmean,dsd)
 {

R/V.gauss.R

@@ -16,7 +16,7 @@
 #' @param dmean Derivative in respect to the parameter vector of the mean function of the distribution
 #' @param dsd Derivative in respect to the parameter vector of the standard deviation function of the distribution 
 #' @return V Matrix
-#' 
+#' @export V.gauss
 #' @author Francois Pelletier
 V.gauss <- function(param,Y,meanf,variancef,skewnessf,kurtosisf,dmean,dsd)
 {

R/Wald.Test.R

@@ -15,7 +15,7 @@
 #' @param eqn.gradient Gradient matrix of the estimating equations
 #' @param alpha level of confidence
 #' @return A list containing the statistic, p-value and reject of the null hypothesis
-#' 
+#' @export Wald.Test
 #' @author François Pelletier
 Wald.Test <- function(param,n,R,r,eqn.covariance,eqn.gradient,alpha=0.05)
 {

R/a.Crowder.Mod.R

@@ -13,7 +13,7 @@
 #' @param dmean Derivative in respect to the parameter vector of the mean function of the distribution
 #' @param dsd Derivative in respect to the parameter vector of the standard deviation function of the distribution
 #' @return First weighting vector
-#' 
+#' @export a.Crowder.Mod
 #' @author Francois Pelletier
 a.Crowder.Mod <- function(param,Y,variancef,dmean,dsd)
 {

R/a.Crowder.R

@@ -14,7 +14,7 @@
 #' @param dmean Derivative in respect to the parameter vector of the mean function of the distribution
 #' @param dsd Derivative in respect to the parameter vector of the standard deviation function of the distribution
 #' @return First weighting vector
-#' 
+#' @export a.Crowder
 #' @author Francois Pelletier
 a.Crowder <- function(param,variancef,skewnessf,kurtosisf,dmean,dsd)
 {

R/a.gauss.R

@@ -10,7 +10,7 @@
 #' @param variancef Variance function of the distribution
 #' @param dmean Derivative in respect to the parameter vector of the mean function of the distribution
 #' @return First weighting vector
-#' 
+#' @export a.gauss
 #' @author Francois Pelletier
 a.gauss <- function(param,variancef,dmean)
 {

R/b.Crowder.Mod.R

@@ -13,7 +13,7 @@
 #' @param dmean Derivative in respect to the parameter vector of the mean function of the distribution
 #' @param dsd Derivative in respect to the parameter vector of the standard deviation function of the distribution
 #' @return First weighting vector
-#' 
+#' @export b.Crowder.Mod
 #' @author Francois Pelletier
 b.Crowder.Mod <- function(param,Y,variancef,dmean,dsd)
 {

R/b.Crowder.R

@@ -14,7 +14,7 @@
 #' @param dmean Derivative in respect to the parameter vector of the mean function of the distribution
 #' @param dsd Derivative in respect to the parameter vector of the standard deviation function of the distribution
 #' @return First weighting vector
-#' 
+#' @export b.Crowder
 #' @author Francois Pelletier
 b.Crowder <- function(param,variancef,skewnessf,kurtosisf,dmean,dsd)
 {

R/b.gauss.R

@@ -10,7 +10,7 @@
 #' @param variancef Variance function of the distribution
 #' @param dsd Derivative in respect to the parameter vector of the standard deviation function of the distribution
 #' @return Second weighting vector
-#' 
+#' @export b.gauss
 #' @author Francois Pelletier
 b.gauss <- function(param,variancef,dsd)
 {

R/confidence.interval.QEE.R

@@ -12,7 +12,7 @@
 #' @param covariance Covariance matrix
 #' @param alpha confidence level
 #' @return 3 line matrix with lower bound, estimate and upper bound
-#' 
+#' @export confidence.interval.QEE
 #' @author François Pelletier
 confidence.interval.QEE <- function(param,covariance,n,alpha=0.05)
 {

R/covariance.QEE.R

@@ -12,6 +12,7 @@
 #' @param V Covariance matrix of equations
 #' @param n Sample size
 #' @return Weighted covariance matrix
+#' @export covariance.QEE
 #' @author François Pelletier
 covariance.QEE <- function(M,V,n) ## Omega
 {

R/eqn.Crowder.Mod.R

@@ -14,7 +14,7 @@
 #' @param dmean Derivative in respect to the parameter vector of the mean function of the distribution
 #' @param dsd Derivative in respect to the parameter vector of the standard deviation function of the distribution
 #' @return The vector value of the estimating equation
-#' 
+#' @export eqn.Crowder.Mod
 #' @author Francois Pelletier
 eqn.Crowder.Mod <- function(param,Y,meanf,variancef,dmean,dsd)
 {

R/eqn.Crowder.R

@@ -16,7 +16,7 @@
 #' @param dmean Derivative in respect to the parameter vector of the mean function of the distribution
 #' @param dsd Derivative in respect to the parameter vector of the standard deviation function of the distribution
 #' @return The vector value of the estimating equation
-#' 
+#' @export eqn.Crowder
 #' @author Francois Pelletier
 eqn.Crowder <- function(param,Y,meanf,variancef,skewnessf,kurtosisf,dmean,dsd)
 {

R/eqn.gauss.R

@@ -14,7 +14,7 @@
 #' @param dmean Derivative in respect to the parameter vector of the mean function of the distribution
 #' @param dsd Derivative in respect to the parameter vector of the standard deviation function of the distribution
 #' @return The vector value of the estimating equation
-#' 
+#' @export eqn.gauss
 #' @author Francois Pelletier
 eqn.gauss <- function(param,Y,meanf,variancef,dmean,dsd)
 {

R/gammaf.Crowder.Mod.R

@@ -9,7 +9,7 @@
 #' Gamma function used in Modified Crowder Estimating Equations
 #' @param Y Individual data sample
 #' @return Gamma function value
-#' 
+#' @export gammaf.Crowder.Mod
 #' @author Francois Pelletier
 gammaf.Crowder.Mod <- function(Y)
 {

R/gammaf.Crowder.R

@@ -11,7 +11,7 @@
 #' @param skewnessf Skewness function of the distribution
 #' @param kurtosisf Kurtosis function of the distribution
 #' @return Gamma function value
-#' 
+#' @export gammaf.Crowder
 #' @author Francois Pelletier
 gammaf.Crowder <- function(param,skewnessf,kurtosisf)
 {

R/obj.Crowder.Mod.R

@@ -14,7 +14,7 @@
 #' @param dsd Derivative in respect to the parameter vector of the standard deviation function of the distribution
 #' @param Q Weight matrix
 #' @return The value of the quadratic form
-#' 
+#' @export obj.Crowder.Mod
 #' @author Francois Pelletier
 obj.Crowder.Mod <- function(param,Y,meanf,variancef,dmean,dsd,Q=diag(4))
 {

R/obj.Crowder.R

@@ -16,7 +16,7 @@
 #' @param dsd Derivative in respect to the parameter vector of the standard deviation function of the distribution
 #' @param Q Weight matrix
 #' @return The value of the quadratic form
-#' 
+#' @export obj.Crowder
 #' @author Francois Pelletier
 obj.Crowder <- function(param,Y,meanf,variancef,skewnessf,kurtosisf,dmean,dsd,Q=diag(4))
 {

R/obj.gauss.R

@@ -14,7 +14,7 @@
 #' @param dsd Derivative in respect to the parameter vector of the standard deviation function of the distribution
 #' @param Q Weight matrix
 #' @return The value of the quadratic form
-#' 
+#' @export obj.gauss
 #' @author Francois Pelletier
 obj.gauss <- function(param,Y,meanf,variancef,dmean,dsd,Q=diag(4))
 {