similar to: Time Series Count Models

Hi, I need to generate the time series of the production, but as I'm new to this topic I am not able to do that. This is what the time series should be: PROD(t)=PROD(t,T) PROD(t-1)=PROD(t-1,T) PROD(t-2)=PROD(t-1)*PROD(t-2,T-1)/PROD(t-1,T-1) PROD(t-3)=PROD(t-2)*PROD(t-3,T-2)/PROD(t-2,T-2) ... ... ... from PROD(t-2)...it will get the same expression; where PROD(t,T) is the value of the

What is the R way of computing cumulative growth rates given a series of discrete values indexed . For instance, given a matrix of 20 observations for each of 5 series (zz), what is the most straight forward technique in R for computing cumulative growth (zzcum) ? It seems for the solution I'm after might be imbedding the following cum growth rate calc as a function into a function call

Dear R users, someone knows how to remove auto-correlation from a frequencies time series? I've tried by differencing (lag 1) the cumulative series (in order to have only positive numbers) , but I can't remove all auto-correlation. If it's useful I can send my db. x <- # autocorrelated series new1<-cumsum(x) new2<-diff(new1,lag=1,differences = 1) acf(new2) #

Dear List, ? I want to fit a CPH survival model with a time-dependent cumulative exposure variable. More specifically, I have exposure measurements for all cohort members at discrete times (yearly measurements) during follow-up. ? I suppose that when estimating the model parameters the most correct would be to have the cumulative exposure for everybody at risk at each death time, as I cannot

I have a data set like the following: subject visit x1 1 1 0.5 1 2 1.2 1 3 0.7 2 1 0.4 2 2 0.6 2 3 1.0 ..... where x1 is the interval between the two visits. Now I want to calculate the cumulative intervals since the beinging, for example subject visit x1 cum 1 1 0.5 0.5 1 2 1.2 0.5+1.2 1 3 0.7 0.5+1.2+0.7 2 1 0.4 0.4 2 2 0.6 0.4+0.6 2 3 1.0 0.4+0.6+1.0 ..... is there an easy to generate the

Dear R users. I have zoo object "size_june" containing market-capital values: > dim(size_june) # market-cap data of 625 firms for 20 years [1] 20 625 > class(size_june) [1] "zoo" > size_june # colnames = "size.firmcode" size.34020 size.4710 size.11050 size.10660 size.9540 size.8060 size.16160 size.8080 size.9280 1988-06-30 NA

I have a dataframe with many firm-year observations and many variables. Not all firms have information for all the years. I want another dataframe with only those firms that have information all years. This is, I want a balanced panel data, but with the maximum number of years. In my reprocucible example I want to keep firms 1,2 and 3 (period 2000 to 2004). I need your help to create a

Hi everyone! Thank you for the help you have been given to me, and here I'm with another problem with my dataframes: I have two dataframes (with much more observations), like these: Dataframe1 Firm Year cash 500400200 2007 100 500400200 2006 200 500400200 2005 400 500400300 2007 300 500400300 2006 240 500400300 2005 120 500400400

Dear all, I am trying to find the solution for the optimization problem focused on the finding minimum cost. I used the solution proposed by excel solver, but there is a restriction in the number of variables. My data consists of 300 rows represent cities and 6 columns represent the centres. It constitutes a cost matrix, where the cost are distances between each city and each of six centres. ..+

Hi, all ecdf function (Empirical Cumulative Distribution Function) in "stats" package counts from smaller values to larger values. However, I want to draw it by counting from larger value to smaller values and I couldn't find options for this purpose. How can I draw ecdf or ecdf like graph by counting from larger values to smaller values. Thank you in advance. Hyunchul Kim

Hello world, I am actually transferring a course in data management for students in biology, geography and agriculture from statistica to R - it works surprisingly well. If anyone is interested in my scratch/notepad (in German language), please see www.hydrology.uni-kiel.de/~schorsch/statistik/statistik_datenauswertung.pdf (pages 40-52) The dataset is:

Hi there, I have a huge data set with multiple firms years and other firm characteristics. I want to run a regression on the dependent variable and other explanatory variables and calculate the residual terms by grouping the firms in same year and same industry. What I want to do is to divide my obseravtion into sub sample that contains the observation with same fiscal year(FYEAR=1990) and same

Hi I would like to plot bar charts in a particular way. The intervals are not evenly distributed and are in a data frame column called size and the relative frequencies are in a second column called mass. Both size and mass are continuous ratio data to all intents and purposes. The data actually represents sieving of sand where $size is sieve aperture and where $mass is the amount remaining on

Dear R-user, a few weeks ago I consulted the list-serve with a similar question. However, my task changed a little but sufficiently to get lost again. So I would appreciate any help on the following issue. I use the plm package and work with firm-level data in a panel. I would like to eliminate all firms that do not fulfill the requirement of having an observation in every variable used for at

I need help in subseting a dataframe: data1<-data.frame(year=c(2001,2002,2003,2004,2001,2002,2003,2004, 2001,2002,2003,2004,2001,2002,2003,2004), firm=c(1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,4),x=c(11,22,-32,25,-26,47,85,98, 101,14,87,56,12,43,67,54), y=c(110,220,302,250,260,470,850,980,1010,140,870,560,120,430,670,540)) data1 I want to keep the firms where all x>0 (where there are

Hi, I have recently use the strucchange package in R with a single time series observation. I found it extremely useful in the testing of change points. Now, I am thinking of using the strucchange package with panel data (about 500 firms, with 73 monthly time series observations each). For each firm, I have to conduct the Fstats and breakpoints tests. Based on the test of each firm, I have to

I have a file with 4 columns per line, all pipe delimited. $ wc -l cmie_firm_data.text 89325 cmie_firm_data.text $ ls -al cmie_firm_data.text -rw-r--r-- 1 ajayshah ajayshah 4415637 Jul 5 15:25 cmie_firm_data.text $ awk -F\| '(NF != 4)' cmie_firm_data.text $ head cmie_firm_data.text All figures are for the year 20030331||| Company|GVA Less Interest (Rs. thousand)|Interest (Rs.

Folks, I have a situation with many firms, observed for many years (but it's not panel data, so every now and then data for a firm just goes missing). Let me show you an example. There are 3 firms "a", "b" and "c". There are 3 years: 1981, 1982 and 1983. There's a factor f which takes values 1, 2 or 3. set.seed(5) D = data.frame( names=c("a",

Dear list, I have a question about the interaction between R code and Latex language trough the Sweave function in the package "utils". What I'm trying to do is to write a report. Contrary to the examples shown in the Sweave Manual in which table already constructed by R are "exported" on Latex files, what I would like to do is to build a table in which I combine text and

Hi, all! Anyone know an easy way to specify the following model. Panel dataset, with stock through time, by firm. I want to run a model of y on a bunch of explanatory variables, and one dummy for each firm, which is 1 for observations that come from firm i, and 0 everywhere else. I have over 200 firms (and a factor variable that contains a firm identifier). Any easy way of going about