similar to: R package checking error.

Dear useRs, I am trying to build my package (nonpareff) which deals with some models of data envelopment analysis. The building worked well, but checking complains when it tests examples. Zipped nonparaeff.Rcheck is attached. Following is the log. --------------------------------------------- arecibo:tmp arecibo$ R CMD build nonparaeff/ * checking for file 'nonparaeff/DESCRIPTION' ...

Dear UseRs, I wrote following function in order to solve Data Envelopment Analysis. Reason for posting is that the function is slow when nrow(dat) is large. I wonder if other functions could substitute the for() loop in the code, such as mapply(). Can anybody help to rewrite the dea() function as efficiently as possible? The code is as follows:

Full_Name: Nuno Monteiro Version: 2.3.1 OS: Windows XP HE Submission from: (NULL) (84.9.38.207) I'm using the FEAR library to perform Data Envelopment analysis with a 36,000 obs dataset. The function dea is working fine but then when I try to use the boot.sw98 to come up with some sensitivity analysis I get the following error:

Sir, Which modules/package should I use to solve the following statistical models: 1. Multiple Objective Programming (MOP) 2. Data Envelopment Analysis (DEA) 3. Lab Experiments 4. Multiple Criteria Decision Making (MCDM) Regards, PS

Dear all, I want to program my own models about Stochastic Frontier Analysis and Linear programming (Data Envelopment Analysis). In this context, is there anyone that may help me with some simple tutorials and scripts about these issues? Thanks a lot. -- Marcus Vinicius Pereira de Souza, Prof. [[alternative HTML version deleted]]

Here''s my comments for the preliminary ZFS Crypto review. - Dan Webrev: http://cr.opensolaris.org/~darrenm/zfs-crypto-gate/webrev/ General comments: DEA-1 - SCCS keywords need to be removed DEA-2 - Copyright updated ------------------------------------------------------------------ usr/src/lib/libcryptoutil/common/keyfile.c pkcs11_read_data() This code in pkcs11_read_data() scares

An embedded and charset-unspecified text was scrubbed... Name: n?o dispon?vel URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20080528/96325940/attachment.pl>

Always via logical expressions. In this case you can use the logical expression myDF$b != "0" to give you a vector of TRUE/FALSE B. > On Sep 25, 2017, at 8:00 AM, Shane Carey <careyshan at gmail.com> wrote: > > This is super, really helpfull. Sorry, one final question, lets say I wanted to remove 0's rather than NAs , what would it be? > > Thanks >

Hi, I am wondering how I should interpreate the output of optFederov() in AlgDesign. Specially I want to know what is $D, $A, $Ge and $Dea, which one I can use as an efficiency to say how good the optimal design is. I only know when a orthogonal design comes, $D = 1. I red the pdf document -- vignette("AlgDesign") [Just type: vignette("AlgDesign") in R, you will get

This is super, really helpfull. Sorry, one final question, lets say I wanted to remove 0's rather than NAs , what would it be? Thanks On Mon, Sep 25, 2017 at 12:41 PM, Boris Steipe <boris.steipe at utoronto.ca> wrote: > myDF <- data.frame(a = c("<0.1", NA, 0.3, 5, "Nil"), > b = c("<0.1", 1, 0.3, 5, "Nil"), >

myDF <- data.frame(a = c("<0.1", NA, 0.3, 5, "Nil"), b = c("<0.1", 1, 0.3, 5, "Nil"), stringsAsFactors = FALSE) # you can subset the b-column in several ways myDF[ , 2] myDF[ , "b"] myDF$b # using the column, you make a logical vector ! is.na(as.numeric(myDF$b)) # This can be used to select the

Hi, Lets say this was a dataframe where I had two columns a <- c("<0.1", NA, 0.3, 5, "Nil") b <- c("<0.1", 1, 0.3, 5, "Nil") And I just want to remove the rows from the dataframe where there were NAs in the b column, what is the syntax for doing that? Thanks in advance On Fri, Sep 22, 2017 at 5:04 PM, Shane Carey <careyshan at

Dear all, I am relatively new to R and have had some difficulty in understanding an error i get when running a code to solve a system of non-linear equations, with four equations and two variables. This is my code: ALPHA <- c(-0.0985168033402, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4) BETA <- c(-0.0985168033402, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4) GAMMA <- c(0.3940672148378, 0.1, 0.15,

Super, Thanks On Fri, Sep 22, 2017 at 4:57 PM, Boris Steipe <boris.steipe at utoronto.ca> wrote: > > a <- c("<0.1", NA, 0.3, 5, "Nil") > > a > [1] "<0.1" NA "0.3" "5" "Nil" > > > b <- as.numeric(a) > Warning message: > NAs introduced by coercion > > b > [1] NA NA 0.3

Santi, In the second line of your function you have the following: f <- numeric(length(x)) This sets the length of this numeric vector (i.e., "f") to the length of the vector "x". Later, inside the function you assign to values to 4 elements of the vector "f". This assumes that "f" is at least 4 element in length. However, you define

Hi, How do I extract just numbers from the following list: a=c("<0.1",NA,0.3,5,Nil) so I want to obtain: 0.3 and 5 from the above list Thanks -- Le gach dea ghui, *Shane Carey* *GIS and Data Solutions Consultant* [[alternative HTML version deleted]]

> a <- c("<0.1", NA, 0.3, 5, "Nil") > a [1] "<0.1" NA "0.3" "5" "Nil" > b <- as.numeric(a) Warning message: NAs introduced by coercion > b [1] NA NA 0.3 5.0 NA > b[! is.na(b)] [1] 0.3 5.0 B. > On Sep 22, 2017, at 11:48 AM, Shane Carey <careyshan at gmail.com> wrote: > > Hi,

Dear R users, I am happy to announce that the R package 'productivity: Indices of Productivity Using Data Envelopment Analysis' is now available on CRAN (https://cran.r-project.org/package=productivity). Productivity allows computing various transitive measures of productivity and profitability, in both levels and changes. In addition to the classic Malmquist productivity index,

Dear R users, I am happy to announce that the R package 'productivity: Indices of Productivity Using Data Envelopment Analysis' is now available on CRAN (https://cran.r-project.org/package=productivity). Productivity allows computing various transitive measures of productivity and profitability, in both levels and changes. In addition to the classic Malmquist productivity index,

Hi, solict excuese if I am reposting I am not sure I properly posted the previous message In the past I have used a DEA package known as "FEAR" on R platform. I could not see that package any more. Instead a new package is there DEA. I kindly apreciate comments or recomendations. Ramilan [[alternative HTML version deleted]]