CRAN Package Check Results for Package prodest

Last updated on 2024-07-14 05:53:40 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.0.1 14.58 118.30 132.88 NOTE
r-devel-linux-x86_64-debian-gcc 1.0.1 8.86 87.44 96.30 NOTE
r-devel-linux-x86_64-fedora-clang 1.0.1 163.39 NOTE
r-devel-linux-x86_64-fedora-gcc 1.0.1 152.18 NOTE
r-devel-windows-x86_64 1.0.1 14.00 107.00 121.00 NOTE
r-patched-linux-x86_64 1.0.1 12.47 114.93 127.40 NOTE
r-release-linux-x86_64 1.0.1 9.90 112.19 122.09 NOTE
r-release-macos-arm64 1.0.1 46.00 NOTE
r-release-macos-x86_64 1.0.1 67.00 NOTE
r-release-windows-x86_64 1.0.1 12.00 107.00 119.00 NOTE
r-oldrel-macos-arm64 1.0.1 49.00 OK
r-oldrel-macos-x86_64 1.0.1 83.00 OK
r-oldrel-windows-x86_64 1.0.1 16.00 120.00 136.00 OK

Check Details

Version: 1.0.1
Check: Rd files
Result: NOTE checkRd: (-1) block.boot.resample.Rd:7: Lost braces; missing escapes or markup? 7 | Function to generate R vectors of resampled IDs. It works reshuffling the row number of the original data - which is stored in the input \code{idvar} along with the relative IDs. The output is a list (N_{i}x1xR), where N_{i} is a random number depending on the reshuffle. | ^ checkRd: (-1) block.boot.resample.Rd:7: Lost braces; missing escapes or markup? 7 | Function to generate R vectors of resampled IDs. It works reshuffling the row number of the original data - which is stored in the input \code{idvar} along with the relative IDs. The output is a list (N_{i}x1xR), where N_{i} is a random number depending on the reshuffle. | ^ checkRd: (-1) checkM.Rd:23: Lost braces 23 | \code{checkM()} accepts one input and - if code{input} is a matrix - returns it without column names, otherwise transforms it into a matrix and returns it without column names. | ^ checkRd: (-1) checkMD.Rd:23: Lost braces 23 | \code{checkMD()} accepts one input and - if code{input} is a matrix - returns it without column names, otherwise transforms it into a matrix and returns it without column names. In case any of the elements of input are different from 0 or 1, it stops the routine and throws an error. | ^ checkRd: (-1) gACF.Rd:47: Lost braces; missing escapes or markup? 47 | \code{gACF()} estimates the second stage of ACF routine. It accepts 7 inputs, generates and optimizes over the group of moment functions E(xi_{it}Z^{k}_{it}). | ^ checkRd: (-1) gACF.Rd:47: Lost braces; missing escapes or markup? 47 | \code{gACF()} estimates the second stage of ACF routine. It accepts 7 inputs, generates and optimizes over the group of moment functions E(xi_{it}Z^{k}_{it}). | ^ checkRd: (-1) gACF.Rd:47: Lost braces; missing escapes or markup? 47 | \code{gACF()} estimates the second stage of ACF routine. It accepts 7 inputs, generates and optimizes over the group of moment functions E(xi_{it}Z^{k}_{it}). | ^ checkRd: (-1) gOPLP.Rd:55: Lost braces; missing escapes or markup? 55 | \code{gOPLP()} estimates the second stage of OP and LP routines. It accepts 7 inputs, generates and optimizes over the group of moment functions E(e_{it}X^{k}_{it}). | ^ checkRd: (-1) gOPLP.Rd:55: Lost braces; missing escapes or markup? 55 | \code{gOPLP()} estimates the second stage of OP and LP routines. It accepts 7 inputs, generates and optimizes over the group of moment functions E(e_{it}X^{k}_{it}). | ^ checkRd: (-1) gOPLP.Rd:55: Lost braces; missing escapes or markup? 55 | \code{gOPLP()} estimates the second stage of OP and LP routines. It accepts 7 inputs, generates and optimizes over the group of moment functions E(e_{it}X^{k}_{it}). | ^ checkRd: (-1) lagPanel.Rd:31: Lost braces; missing escapes or markup? 31 | \code{lagPanel()} accepts three inputs (the ID, the time and the variable to be lagged) and returns the vector of lagged variable. Lagged inputs with no correspondence - i.e., X_{-1} - are returned as NA. | ^ checkRd: (-1) panelSim.Rd:53-55: Lost braces in \itemize; \value handles \item{}{} directly checkRd: (-1) panelSim.Rd:56-58: Lost braces in \itemize; \value handles \item{}{} directly checkRd: (-1) panelSim.Rd:59-61: Lost braces in \itemize; \value handles \item{}{} directly checkRd: (-1) panelSim.Rd:62-64: Lost braces in \itemize; \value handles \item{}{} directly checkRd: (-1) panelSim.Rd:65-67: Lost braces in \itemize; \value handles \item{}{} directly checkRd: (-1) panelSim.Rd:68-70: Lost braces in \itemize; \value handles \item{}{} directly checkRd: (-1) panelSim.Rd:71-73: Lost braces in \itemize; \value handles \item{}{} directly checkRd: (-1) panelSim.Rd:74-76: Lost braces in \itemize; \value handles \item{}{} directly checkRd: (-1) panelSim.Rd:77-79: Lost braces in \itemize; \value handles \item{}{} directly checkRd: (-1) prodestACF.Rd:58: Lost braces; missing escapes or markup? 58 | where \eqn{y_{it}} is the (log) output, w_{it} a 1xJ vector of (log) free variables, k_{it} is a 1xK vector of state variables and \eqn{\epsilon_{it}} is a normally distributed idiosyncratic error term. | ^ checkRd: (-1) prodestACF.Rd:58: Lost braces; missing escapes or markup? 58 | where \eqn{y_{it}} is the (log) output, w_{it} a 1xJ vector of (log) free variables, k_{it} is a 1xK vector of state variables and \eqn{\epsilon_{it}} is a normally distributed idiosyncratic error term. | ^ checkRd: (-1) prodestLP.Rd:60: Lost braces; missing escapes or markup? 60 | where \eqn{y_{it}} is the (log) output, w_{it} a 1xJ vector of (log) free variables, k_{it} is a 1xK vector of state variables and \eqn{\epsilon_{it}} is a normally distributed idiosyncratic error term. | ^ checkRd: (-1) prodestLP.Rd:60: Lost braces; missing escapes or markup? 60 | where \eqn{y_{it}} is the (log) output, w_{it} a 1xJ vector of (log) free variables, k_{it} is a 1xK vector of state variables and \eqn{\epsilon_{it}} is a normally distributed idiosyncratic error term. | ^ checkRd: (-1) prodestOP.Rd:60: Lost braces; missing escapes or markup? 60 | where \eqn{y_{it}} is the (log) output, w_{it} a 1xJ vector of (log) free variables, k_{it} is a 1xK vector of state variables and \eqn{\epsilon_{it}} is a normally distributed idiosyncratic error term. | ^ checkRd: (-1) prodestOP.Rd:60: Lost braces; missing escapes or markup? 60 | where \eqn{y_{it}} is the (log) output, w_{it} a 1xJ vector of (log) free variables, k_{it} is a 1xK vector of state variables and \eqn{\epsilon_{it}} is a normally distributed idiosyncratic error term. | ^ checkRd: (-1) prodestROB.Rd:41: Lost braces; missing escapes or markup? 41 | where \eqn{y_{it}} is the (log) output, w_{it} a 1xJ vector of (log) free variables, k_{it} is a 1xK vector of state variables and \eqn{\epsilon_{it}} is a normally distributed idiosyncratic error term. | ^ checkRd: (-1) prodestROB.Rd:41: Lost braces; missing escapes or markup? 41 | where \eqn{y_{it}} is the (log) output, w_{it} a 1xJ vector of (log) free variables, k_{it} is a 1xK vector of state variables and \eqn{\epsilon_{it}} is a normally distributed idiosyncratic error term. | ^ checkRd: (-1) prodestWRDG.Rd:41: Lost braces; missing escapes or markup? 41 | where \eqn{y_{it}} is the (log) output, w_{it} a 1xJ vector of (log) free variables, k_{it} is a 1xK vector of state variables and \eqn{\epsilon_{it}} is a normally distributed idiosyncratic error term. | ^ checkRd: (-1) prodestWRDG.Rd:41: Lost braces; missing escapes or markup? 41 | where \eqn{y_{it}} is the (log) output, w_{it} a 1xJ vector of (log) free variables, k_{it} is a 1xK vector of state variables and \eqn{\epsilon_{it}} is a normally distributed idiosyncratic error term. | ^ checkRd: (-1) prodestWRDG_GMM.Rd:44: Lost braces; missing escapes or markup? 44 | where \eqn{y_{it}} is the (log) output, w_{it} a 1xJ vector of (log) free variables, k_{it} is a 1xK vector of state variables and \eqn{\epsilon_{it}} is a normally distributed idiosyncratic error term. | ^ checkRd: (-1) prodestWRDG_GMM.Rd:44: Lost braces; missing escapes or markup? 44 | where \eqn{y_{it}} is the (log) output, w_{it} a 1xJ vector of (log) free variables, k_{it} is a 1xK vector of state variables and \eqn{\epsilon_{it}} is a normally distributed idiosyncratic error term. | ^ checkRd: (-1) weightM.Rd:51: Lost braces; missing escapes or markup? 51 | \code{weightM()} accepts at least 7 inputs: Y, X1, X2, Z1, Z2, betas and numR. With these, computes the optimal weighting matrix in a system GMM framework, i.e. W* = sigma*Z'Z. If it is called during the first stage, it returns W*, otherwise will return an estimate of the parameters' standard errors, i.e., the square root of the diagonal of the variance-covariance matrix: 1/N( (X'Z) W* (Z'X) )^{-1}. | ^ Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64