similar to: Optimizing

Hi, I am new to R. My problem is with the ordered logistic model. Here is my question: Generate an order discrete variable using the variable wrwage1 = wages in first full calendar quarter after benefit application in the following way: * wage*1*Ordered *= 1 *if*0 *· wrwage*1 *< *1000 2 *if*1000 *· wrwage*1 *< *2000 3 *if*2000 *· wrwage*1 *< *3000 4 *if*3000 *· wrwage*1 *<

Dear all, I have 1980~1990 eleven datas, every year have three variables, wage gender(1=female, 2=male) race(1=black, 2=white) My original commands is: fig2b<-reldist(y=mu1990$wage,yo=mu1980$wage,.......) I have three questions: 1. If I want to appoint y=women's wage in 1990 yo=women's wage in 1980 2. If I want to appoint y=women's wage in

Suppose we observe N individuals, for each of which we have a time-series. How do we correctly create a lagged value of the time-series variable? As an example, suppose I create: A <- data.frame(year=rep(c(1980:1984),3), person= factor(sort(rep(1:3,5))), wage=c(rnorm(15))) > A year person wage 1 1980 1 0.17923212 2 1981

I am trying to simulate the trajectory of the pension assets of one person. In C-like syntax, it looks like this: daily.wage.growth = 1.001 # deterministic contribution.rate = 0.08 # deterministic 8% Wage = 10 # initial Asset = 0 # initial for (10,000 days) { Asset += contribution.rate * Wage

Hello list, I'm following the paper (http://www.jstatsoft.org/v27/i02/paper) on how to use "plm" to run panel regressions, and am having trouble with what I believe should be something very basic. When I run the command (p.9 in the paper): R> dynformula(emp~wage+capital,log=list(capital=FALSE,TRUE),lag=list(emp=2,c(2,3)),diff=list(FALSE,capital=TRUE)) I see: emp ~ wage +

Dear John Fox, Christian Kleiber, and Achim Zeileis, I am attempting to run various independent variable parameters to assess their suitability. Unfortunately, I hit a snag and couldn't get the tests to run properly. When I used ivreg, I got an error message saying: "Error in eval(predvars, data, env) : object 'WageInequality' not found." Can you please help? Model:

Hi, I'm trying to do a regression like this: wage.r = lm( log(WAGE) ~ log(EXPER) where EXPER is an integer that goes from 0 to about 50. EXPER contains some zeros, so you can't take its log, and the above regression therefore fails. I would like to make R accept log(0) as 0, is that possible? Or do I have first have to turn the 0's into 1's to be able to do the above

Hello, I have a set of data including age, wage and education level each called age76, wage76 and grade76 I want to know how i can calculate the average wage of people age 15 to 65 (each year separetly) , only for those who have an education level of 10 12 and 16... -- View this message in context: http://r.789695.n4.nabble.com/Conditional-average-tp4585313p4585313.html Sent from the R help

Dear R-List, My questions concerns missing values. Specifically, is is possible to use different "types" of missingness in a dataset and not a one-size-fits-all NA? For example, data may be missing because of an outright refusal by a respondent to answer a question, or because she didn't know an answer, or because the item simply did not apply. In later analysis it is sometimes

If I have matrics as follows: > a <- c(1,1,0,0) > b <- c(4,4,0,0) > c <- c(3,5,5,6) How can I use R code to solve the equation ax^2+bx+c=0. thanks! yuying shi [[alternative HTML version deleted]]

Dear friends, I am trying to understand and implement instrumental variables regression using R. I found a small (simple) example here which purportedly illustrates the mechanics (using 2-stage least-squares): http://www.r-bloggers.com/a-simple-instrumental-variables-problem/ Basically, here are the R commands (reproducible example) from that site: # ------ begin R library(AER)

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I have some square matrices with na values in corresponding rows and columns. M<-matrix(1:2,10,10) M[6,1:2]<-NA M[10,9]<-NA M<-as.matrix(as.dist(M)) print (M) 1 2 3 4 5 6 7 8 9 10 1 0 2 1 2 1 NA 1 2 1 2 2 2 0 1 2 1 NA 1 2 1 2 3 1 1 0 2 1 2 1 2 1 2 4 2 2 2 0 1 2 1 2 1 2 5 1 1 1 1 0 2 1 2 1 2 6 NA NA 2 2 2 0 1 2 1 2 7 1 1 1 1 1 1 0 2 1 2 8

Dear R users, I had a research question which involves a simultaneous equation system, one is the common continuous dependent variable, y1, say wage, or log wage, another one is a latent variable, y*, which I only observe up to a ordinal scale, say attitudes toward a problem, taking values as y2= 1, 2, 3 or 4. Both of them have other exogeneious variables. I have been search on internet for

hi, I use R - 2.15(32bit), and want to make a code to clear a console. Actually, I used to run following code to do that but after update the version of R from 2.14 to 2.15, it doesn't work. cls <- function (t) { require(RDCOMClient) wsh <- COMCreate("Wscript.Shell") wsh$SendKeys("\f") invisible(wsh) } cls() or cls <-

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Dear R-Helpers, I'm working with immunoassay data and 5PL logistic model. I wanted to experiment with different forms of weighting and parameter selection, which is not possible in instrument software, so I turned to R. I am using R 2.14.2 under Win7 64bit, and the 'nls' library to fit the model - I started with the same model and weighting type (1/y) as in the instrument to see

Hello, I am using {plm} to estimate panel models. I want to estimate a model that includes fixed effects for time and individual, but has a random individual effect for the coefficient on the independent variable. That is, I would like to estimate the model: Y_it = a_i + a_t + B_i * X_it + e_it Where i denotes individuals, t denotes time, X is my independent variable, and B (beta) is the

Hello, I am having problems vectorizing the following (i/o using a for/next/while loop): I have 2 sequences such as: x, y 1, 30 2, -40 0, 50 0, 25 1, -5 2, -10 1, 5 0, 40 etc etc The first sequence (x) takes integer numbers only: 0, 1, 2 The sequence y can be anything... I want to be able to retrieve (in a list if possible) the 3 last values of the y sequence before a value of 1 is

I search an plugin or gem, but don''t find nothing satisfactory. I believe to be stranger a technology that nails the DRY, have that create you vary equal tables, instead of using inheritance. Exists an soluction for this? I want a solution similar to this: create_table :people |t| do t.column :name t.column :address end create_table :customer |t| do t.column :person_id