version 1.0.0

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: hyperbolicDEA
 Title: Hyperbolic DEA Estimation
-Version: 0.1.1
+Version: 1.0.0
 Authors@R: c(
     person("Alexander", "Öttl", , "alexoettl34@gmail.com", role = c("cre", "aut"),
            comment = c(ORCID = "0000-0002-0734-4135")),
@@ -16,8 +16,8 @@ Config/testthat/edition: 3
 Encoding: UTF-8
 RoxygenNote: 7.2.3
 NeedsCompilation: no
-Packaged: 2024-02-21 12:28:23 UTC; fkg114
+Packaged: 2024-03-18 16:57:34 UTC; fkg114
 Author: Alexander Öttl [cre, aut] (<https://orcid.org/0000-0002-0734-4135>),
   Daniel Gulde [aut]
 Repository: CRAN
-Date/Publication: 2024-02-22 20:20:03 UTC
+Date/Publication: 2024-03-18 17:30:07 UTC

MD5

@@ -1,14 +1,18 @@
-d7f9a76f9ebd9f4ec1f5d6c6f783345e *DESCRIPTION
+f72375bffd457cb3fe5117eed9b9d8f0 *DESCRIPTION
 7420c3435de96c603a7eac5974e3ad63 *LICENSE
-c581dc6070df1c1f2ede2c134dcf3e5c *NAMESPACE
-5e4bae93b128521236d3f65a103c7a48 *R/costDEA.R
-7a5e183093294fd45ccce42f16305923 *R/hyperbolicDEA.R
-9a1bfa1b34f83cbff9affe2afb55718a *R/lprofitDEA.R
-4a944f9d71399c98794a6456d8679a90 *R/nlprofitDEA.R
+40d288bb253f218da700a696ab844b8e *NAMESPACE
+f431ca48123e257e4df594362349b979 *R/check_arguments.R
+3fd393a145c4f09922dfb8c4ccfdb803 *R/costDEA.R
+ca59a30e41c94608ba12ec8818db485a *R/hyperbolicDEA.R
+94478f63edbcb40cdab42a6f488cceb6 *R/lprofitDEA.R
+bb6ae3c0c6f9e60b8294856ad30c6080 *R/nlprofitDEA.R
+c0be7b6dc48e621146ab64b145af7d1b *R/slack.R
+7590bcef71201e0535bdfe9405280ae4 *R/wrDEA.R
 49322e18bc98f2e01f48873107d43f6b *README.md
-75a4f572ac6ed3c7f7cb50b6f3b2a934 *man/costDEA.Rd
-5301a3ef1a0dcf4b6f77e64099c72a20 *man/hyperbolicDEA.Rd
-da825138fe98080f7706cd658623d31a *man/lprofitDEA.Rd
-e1abb9bbf539f08fff7a570f5a2461e9 *man/nlprofitDEA.Rd
+2c2a5c42b855f23499c159842bffe2a9 *man/costDEA.Rd
+de66a1215cef333db63c1f1c93b96867 *man/hyperbolicDEA.Rd
+33dfe4ebef753d02d8da9e22458bb6d5 *man/lprofitDEA.Rd
+e4ccd6da57bb2111dc2be22d6ebca7ff *man/nlprofitDEA.Rd
+153b2b504257309308a9f25cde35b062 *man/wrDEA.Rd
 5eb9c7385ddd9a0f93218d310178b677 *tests/testthat.R
-138e001fe5d422d50412e43b8b89fbd8 *tests/testthat/test-hyperbolicDEA.R
+4af076af8dd051d1e74bb66bbc4a2e6e *tests/testthat/test-hyperbolicDEA.R

NAMESPACE

@@ -4,6 +4,7 @@ export(costDEA)
 export(hyperbolicDEA)
 export(lprofitDEA)
 export(nlprofitDEA)
+export(wrDEA)
 import(Benchmarking)
 import(doParallel)
 import(dplyr)

R/check_arguments.R

@@ -0,0 +1,69 @@
+check_arguments <- function(X, Y, XREF = NULL, YREF = NULL, 
+                            WR = NULL, RTS = "vrs", 
+                            NONDISC_IN = NULL, NONDISC_OUT = NULL, 
+                            ALPHA = NULL, ORIENTATION = NULL){
+
+  # General checks for all functions in the package
+  if (!is.matrix(X) && !is.data.frame(X) && !is.numeric(X)){
+    stop("X must be a numeric vector, matrix or dataframe")
+  }
+  if (!is.matrix(Y) && !is.data.frame(Y) && !is.numeric(Y)){
+    stop("Y must be a numeric vector, matrix or dataframe")
+  } 
+
+  if (!is.null(WR)){
+    if (!is.matrix(WR) && !is.data.frame(WR)){
+      WR <- t(as.matrix(WR))
+    } 
+    if (ncol(WR) != ncol(as.matrix(X)) + ncol(as.matrix(Y))){
+      stop("WR must be a matrix of weight restrictions in standard form,
+           ncol(WR) = ncol(Y) + ncol(X)")
+    }
+  }
+  if (!is.null(XREF)&&!is.null(YREF)){
+    if (!is.matrix(XREF) && !is.data.frame(XREF) && !is.numeric(XREF)){
+      stop("XREF must be a numeric vector, matrix or dataframe")
+    } 
+    if (!is.matrix(YREF) && !is.data.frame(YREF) && !is.numeric(YREF)){
+      stop("YREF must be a numeric vector, matrix or dataframe")
+    } 
+    if ((ncol(as.matrix(YREF))+ncol(as.matrix(XREF))) != (ncol(as.matrix(X)) + ncol(as.matrix(Y)))){
+      stop("XREF and YREF must be the same input-output combination:
+           ncol(XREF) = ncol(X); ncol(YREF) = ncol(Y)")
+    }
+  }  
+  if (anyNA(X) || anyNA(Y) || anyNA(XREF) || anyNA(YREF) || anyNA(WR) ||
+      any(is.nan(X)) || any(is.nan(Y)) || any(is.nan(XREF)) || 
+      any(is.nan(YREF)) || any(is.nan(WR))) {
+    stop("The optimizer cannot handle missing or NaN values.")
+  }
+
+  possible_rts <- c("crs", "vrs", "ndrs", "nirs", "fdh")
+  RTS <- tolower(RTS)
+  if (!(RTS %in% possible_rts)){
+    stop("Unknown scale of returns:", RTS)
+  }
+  if (!is.null(ALPHA)){
+    if (ALPHA < 0 || ALPHA > 1){
+      warning("ALPHA should be a number between 0 and 1 otherwise inputs can be increased
+            or outputs can be decreased")
+    }
+  }
+  if (!is.null(ORIENTATION)){
+    ORIENTATION <- tolower(ORIENTATION)
+    if (!(ORIENTATION %in% c("in", "out"))){
+      stop("ORIENTATION must be either 'in' or 'out'")
+    }
+  }
+  if (!is.null(NONDISC_IN)){
+    if (!(all(NONDISC_IN %in% 1:ncol(as.matrix(X))))){
+      stop("NONDISC_IN must be an available index of the input matrix")
+    } 
+  }
+  if (!is.null(NONDISC_OUT)){
+    if (!(all(NONDISC_OUT %in% 1:ncol(as.matrix(Y))))){
+      stop("NONDISC_OUT must be an available index of the output matrix")
+    } 
+  }
+
+}

R/costDEA.R

@@ -1,17 +1,20 @@
 #' @title Cost DEA model
 #' @description Cost DEA model optimizing the input allocation with given prices.
-#' It returns the estimated lambdas as well as the optimal values for inputs.
+#' It returns the estimated lambdas as well as the optimal values for inputs and a cost efficiency score
+#' that is the ratio of optimal costs over observed costs.
 #' 
-#' @seealso [Benchmakring::cost.opt] for a similar function
+#' @seealso [Benchmarking::cost.opt] for a similar function
 #'
-#' @param X Matrix or dataframe with DMUS as rows and inputs as columns
-#' @param Y Matrix or dataframe with DMUs as rows and outputs as columns
-#' @param pX Matrix or dataframe with prices for each DMU and input.
-#' Therefore it mus have the same dimensions as X.
-#' @param RTS Character string indicating the returns-to-scale, e.g. "crs", "vrs"
-#' @return A list object containing cost optimal inputs and lambdas indiceting
-#' the the peer for optimal input allocation. Additionally, it returns the cost 
-#' efficiency as the ratio of the optimal cost to the observed cost.
+#' @param X Vector, matrix or dataframe with DMUs as rows and inputs as columns
+#' @param Y Vector, matrix or dataframe with DMUs as rows and outputs as columns
+#' @param pX Vector, matrix or dataframe with prices for each DMU and input.
+#' Therefore it must have the same dimensions as X.
+#' @param RTS Character string indicating the returns-to-scale, e.g. "crs", "vrs".
+#' 
+#' @return A list object containing the following:
+#' \item{lambdas}{Estimated values for the composition of the respective Benchmarks. The lambdas are stored in a matrix with dimensions nrow(X) x nrow(X), where the row is the DMU under observation and the columns are the peers used for the Benchmark.}
+#' \item{opt_value}{Optimal inputs.}
+#' \item{cost_eff}{Cost efficiency as the ratio of the optimal cost to the observed cost.}
 #' @examples
 #' X <- matrix(c(1,2,3,3,2,1,2,2), ncol = 2)
 #' Y <- matrix(c(1,1,1,1), ncol = 1)
@@ -24,7 +27,7 @@
 #' @import lpSolveAPI
 #' @export
 
-costDEA <- function(X, Y, pX, RTS = "vrs") {
+costDEA <- function(X, Y, pX, RTS = "crs") {
 
   # Check arguments given by user 
   if (!is.matrix(X) && !is.data.frame(X) && !is.numeric(X)){
@@ -112,7 +115,7 @@ costDEA <- function(X, Y, pX, RTS = "vrs") {
 
   }
 
-  colnames(lambdas) <- c(paste("Lambda",1:ncol(in_out_data),sep=""))
+  colnames(lambdas) <- c(paste("L",1:ncol(in_out_data),sep=""))
   colnames(opt_value) <- c(paste("X",1:ncol(X),sep=""))
 
   # Estimate cost efficiency