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Hi, I am trying to write a for loop with if else statements to calculate biomass density estimates for different types of sampling gear. My code is: bmd=for (i in 1:length(Gear)){ if (Gear==20) {bioden=Biomass/141} else {if (Gear==23) {bioden=Biomass/68}} else {if (Gear==160) {bioden=Biomass/4120}} else {if (Gear==170) {bioden=Biomass/2210}} else {if (Gear==300)

Hello, If I have two variables that are factors or characters and I want to create a new variable that is the combination of both what function can I use to accomplish this? Ex. Var1 Var2 SA100055113 19851113 And I want NewVar SA10005511319851113 Thanks in advance. Cameron Guenther, Ph.D. Associate Research Scientist FWC/FWRI, Marine Fisheries Research 100 8th Avenue S.E. St.

Hello, I have sample data set that looks like: YEAR MONTH DAY CONTINUE SPL TIMEFISH TIMEUNIT AREA COUNTY DEPTH DEPUNIT GEAR TRIPID CONVUNIT 1992 1 26 1 SP0073928 8 H 7 25 4 NA 1000000 02163399054 161 1992 1 26 1 SP0073928 8 H 7 25 4 NA 1000000 02163399054 8 1992 1 26 2 SP0004228 8 H 7 25 4 NA 1000000 02163399054 161 1992 1 26 2 SP0004228 8 H 7 25 4 NA 1000000 02163399054 8 1992

Hello everyone, I have a large dataset (x) with some rows that have duplicate variables that I would like to remove. I find which rows are the duplicates with X1<-which(duplicated(x)). That gives me the rows with duplicated variables. Now, how can I remove just those rose from the original data frame. I think I can create a new data frame without the duplicates using subset. I have tried:

Hello everyone, If I have an incidence matrix of 0 and 1's P=[1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 0 0 0 1 1 1 0 0 0 1 1 0 0 0 0] I want to create a new uniform random matrix [a] that is filled with 0's and 1's but constrained so that the row and column sums are the same as in [P]. Does anyone know how to accomplish this? Thanks in advance Cameron Guenther, Ph.D.

Hello, I have a data set with a grouping variable (TRIPID) and several other variables. TRIPID is repeated in some areas and I would like to use a function like aggregate to sum the variable UNITS according to TRIPID. However I would also like to retain the other variables as they are in the data set with the new summed TRIPID. So what I have is something like this: YEAR MONTH DAY

Hello, I have a data set with a grouping variable (TRIPID) and several other variables. TRIPID is repeated in some areas and I would like to use a function like aggregate to sum the variable UNITS according to TRIPID. However I would also like to retain the other variables as they are in the data set with the new summed TRIPID. So what I have is something like this: YEAR MONTH DAY

Hello, I have a much larger dataset that is similar in form to: year species length count 1998 1 150 1 1998 2 200 1 1998 3 250 2 1999 1 150 3 1999 2 200 4 1999 3 250 5 2000 1 150 1 2000 2 200 1 2000 3 250 1 2001 1 150 2 2001 2 200 3 2001

Hello, I am using the glm model with a poisson distribution. The model runs just fine but when I try to get the null deviance for the model of the null degrees of freedom I get the following errors: > null.deviance(pAmeir_1) Error: couldn't find function "null.deviance" > df.null(pAmeir_1) Error: couldn't find function "df.null" When I do: >

Hello, Suppose I have a matrix a where a= sp1 sp2 sp3 sp4 sp5 sp6 site1 1 0 1 1 0 1 site2 1 0 1 1 0 1 site3 1 1 1 1 1 1 site4 0 1 1 1 0 1 site5 0 0 1 0 0 1 site6 0 0 1 0 1 0 And I want to pack that matrix so that the upper left corner contains most of the ones and the bottom right corner contains most of the zeros so that matrix b is b= sp3 sp6 sp4 sp1 sp2 sp5 site1 1 1 1 1 0 0 site2

Hello all, I hope someone can help me with this. I have function that calculates two values based on input data. A simple example follows: test<-function(x,s,rangit=seq(0,10,1)) { rangit<-rangit y<-vector() p<-vector() for(i in 0:length(rangit)){ y[i]<-x+s[1]+rangit[i] p[i]<-x+s[2]+rangit[i] } return(data.frame(rangit,y,p)) } And returns the following: rangit y p 1

Hello everyone, I have a function here that I wrote but doesn't seem to work quite right. Attached is the code. In the calib funcion under the for loop Bt[i+2]<-(1-m)*Bt[i+1]+Rt[i]*Rerr-Ct[i+1] returns NA's for everything after years 1983 and 1984. However the code works when it reads Bt[i+2]<-(1-m)*Bt[i+1]+Rt[i]*Rerr-Ct[i]. I don't quite understand why since it should be

Hello everyone, I have a function here that I wrote but doesn't seem to work quite right. Attached is the code. In the calib funcion under the for loop Bt[i+2]<-(1-m)*Bt[i+1]+Rt[i]*Rerr-Ct[i+1] returns NA's for everything after years 1983 and 1984. However the code works when it reads Bt[i+2]<-(1-m)*Bt[i+1]+Rt[i]*Rerr-Ct[i]. I don't quite understand why since it should be

Hi All, If you could help me with this problem I would greatly appreciate it. Suppose I have a matrix A: 1 1 1 1 0 1 1 1 1 1 1 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 0 1 1 0 0 0 0 1 0 0 I would like, for each row, to sum the number of times a 0 appears in front of a 1. So what I would like is to have Sum 1 1 1 1 0 1 1 1 1 1 1 1 1 0 1 0 1 0 0 2 1 0 1 0 0 1 0 0 0 2 1 1 0 0 0 0 1

Hi all, I have a question about expression. In a figure I want to include the term D*obs with the star as as superscript and obs as subscript. I have even just tried to get the star to be superscript. The code I tried was text(Dstar+7,120,expression(paste({}D,^*))), but that doesn't work and I get a syntax error. I can't seem to find anything in the help files that explains it.

Does anyone know if there is a file size limit for inputting a SAS data set? The file size I am trying to import is 184 MB. The code is: >library("foreign") > > sashome<-"C:/Program Files/SAS Institute/SAS/V8" > input.data<-read.ssd( file.path("G:/DATA/Cam/ECPATH/FIM"),"tbm_c", + sascmd=file.path(sashome,"sas.exe")

Hi all, I am hoping someone can help me out with this: If I have dataframe of years and ages and the first column and first row are filled with leading values: Df<- age1 age2 age3 Yr1 1 0.4 0.16 Yr2 1.5 0 0 Yr3 0.9 0 0 Yr4 1 0 0 Yr5 1.2 0 0 Yr6 1.4 0 0 Yr7 0.8 0 0 Yr8 0.6 0 0 Yr9 1.1 0 0 Now the rest of the cells need to be filled according to the previous year and age

Hi everyone, I am trying to construct a glm and am running into a couple of questions. The data set I am using consists of 6 categories for the response and 6 independent predictors representing nutrient concentrations at sample point locations. Ultimately I'd like to use the probabilities for each response category in a simulation model such that these probabilities are used to define a

Hi all, I am having a problem getting my fucntion to work correctly. Here is my problem. I have three ages: Nage<-c(1,2,3) I have an weight matrix: Wt<-c( 0.04952867, 0.23808432, 0.34263880) I have an age schedule of maturity: Mat<-c(0,1,1) where 0 is not mature, and 1 is mature I have a vulnerability schedule: Vul<-c(0,1,1) I have an survivorship schedule:

I have a data set 382 rows and 63 columns. One of the columns is bay, and there are 6 bays. But, the number of levels for this factor is 7 when it should be six because there is some 'blank' level "". When I subset for the blank level "", I get 0 rows. What in my data could be causing this? Thanks. > dim(datmtx) [1] 382 63 > datmtx$bay [1] TB TB