similar to: help with mysql and R: partitioning by quintile

Hi, I am using the package "demography" from Rob Hyndman for the Lee-Carter-Model. It is an amazing powerful tool but I am struggling with one issue: *I want to compute different quintiles for the cumulative survival probability derived from the Lee-Carter-Forecast (e.g. the 50%-quintile, 75%-quintile and 99%-quintile) for the next 10 years. * I am sure the package possess this

Hi, I am trying in R to indicate in which quintile a value of a variable is for every month of my data frame in this case based on volatility. For each month I want to know for each stock if it is in the most volatile quintile of if it is in one of the others. So far I have come up with the following function (see below). Unfortunately, the function only works in some cases and often gives the

Dear All, I am economist and working on poverty / income inequality. I need descriptive statitics like the ratio of education expentitures between different income quintiles where each household has a different weight. After a bit of google search I found 'Hmisc' and 'quantreg' libraries for weighted quantiles. The problem is that these packages give me only weighted quintiles;

Hi, I am looking to build even quintiles for a set of data. I managed to get it done, but I would like to know if there is a more direct way to write the data from my loop output x in the bottom of the code into the "empty" matrix p1, which I filled with NA''s. The way I am doing it at the moment is, more or less adding the matrix x after p1 and then deleting in a second step

Hi all, I am not sure how to handle interactions with categorical predictors in the GAM models. For example what is the different between these bellow two models. Tests are indicating that they are different but their predictions are essentially the same. Thanks a bunch, > gam.1 <- gam(mortality.under.2~ maternal_age_c+ I(maternal_age_c^2)+ + s(birth_year,by=wealth) + +

Hello- I wonder if there's a way to replicate SAS rank procedure where it ranks a variable by a certain number of groups. For example, it's very easy to calculate quintile rank in SAS, but I couldn't find the similar function in R. Does anyone know how to do this? Thanks. -- View this message in context:

Hi All: Greetings, and best wishes from the festive times here at Kolkata, India -- the time of Durga Puja celebrations. I seek your advice as I try plotting lines for my data. The problem: I have created a dataframe that looks like this (name: myFrame): lowest second third fourth highest significance INAS 0.107 0.115 0.123 0.115 0.166 0.000 MMA 0.091 0.107 0.115

I have some output from a survey shown below and would like to insert total rows for each category to then be able to use it as a data set for further analysis. Is it possible to do this in R. In this example I would like to insert a row between rows 5 and 6, 10 and 11, 15 and 16, 20 and 21 and put in the sum of the rows 1-5, 6-10, 11-15, 16-20 and to delete row 21 which has NA in it. I would

Hi, I'm a newbie to R. My knowledge of statistics is mostly self-taught. My problem is how to measure the effect of users in groups. I can calculate a particular attribute for a user in a group. But my hypothesis is that the user's attribute is not independent of each other and that the user's attribute depends on the group ie that user's behaviour change based on the group. Let

Hi, I have the following data about courses (504) in a university, two attributes about the proportion of resources used (#resources_used / #resources_available), namely the average and the standard deviation. Thus I have: [1] n=504 rows [2] 1 id column and 2 attributes Here's a sample of the data: courseid,average,std 12741,1,0 17161,1,0 12514,1,0

Hi, I want to do a visualisation of a matrix plot made up of several plots of correlation matrices (using corrplot()). My data is in csv format. Here's an example: id,category,attribute1,attribute2,attribute3,attribute4 661,SCHS,43.2,0,56.5,1 12202,SCHS,161.7,5.7,155,16 1182,SCHS,21.4,0,29,0 1356,SSS, 8.8182,0.1818,10.6667,0.6667 1864,SCHS,443.7273,9.9091,537,46 12360,SOA,6.6364,0,10,0

Hi, Newbie here. I read the R for Beginners but i still don't get this. I have the following data (this is just an example) in a CSV file: courseid numstudents 101 209 141 13 246 140 263 8 321 10 361 10 364 28 365 25 366 23 367

Hi everyone, I'm experiencing difficulty getting the results I want when I use a nested for loop. I have a data set to which I perform some calculations, and then try to apply a regression over a rolling window. The code runs, but the regression results I am getting (intercept and slope) are simply the same, repeated again and again in the results matrix. The regression does not seem to be

Hello, Hope that someone could help me plotting longitudinal data below: 7213 3333330001 0.8300 13.05.09 1 1 3333330001 0.8700 09.02.05 NULL 4797 3333330001 0.7700 21.03.07 NULL 2399 3333330001 0.7800 12.04.06 NULL 2400 3333330002 NULL 27.03.06 NULL 7230 3333330002 0.8200 14.05.09 0 2 3333330002 0.8400 09.02.05 NULL 4798 3333330002 0.8700 20.03.07 0 4799 3333330003 0.9000 20.03.07 13 2401

Hello All, I am trying to color five subsets of points in a series of vertical strip charts by quintiles using the quantile function, but I have not been able to do this successfully, nor have I been able to find an example of this online. I would like to have the "E1", "E2", and "E3" columns plotted on a single plot (containing the three strip charts). I am

Hi, This is not meant to be critical of R, but is intended as a possible source for improvements to R. SAS needs the competition. I am reasonably knowledgeable about R SAS-(all products including IML) SAS and R run on Windows(all flavors) UNIX(all flavors) Apple OSs Does R run on natively (no emulation)? We have quite a few users on these systems VAX-VMS Z-OS (mainframe) MVS VM/CMS(IBM)

Hola chic en s, alguien con experiencia en propensión score matching? Planteo duda: Clasicamente el PSM se ha utilizado en un intento de homogeneizar cohortes de enfermos quienes han estado ?expuestos? a un tratamiento x Vs aquellos que no han estado expuestos (no expuestos). Esto aplica para medicamentos o procedimientos quirúrgicos o no. Bien, En algún articulo he leído que el PSM se puede

I used points graphic (geoR) in this way: points(zn,pt.divide=c("quintiles"), main="Location map of Zn",lambda=1,col="gray",yl="coord y",xl="coord x",x.leg=0. 3, y.leg=5.5,dig.leg=2,cex.min=0.5,cex.max=1,) Can I reduce legend characters (a sort of cex)?

Hola chic en s, alguien con experiencia en propensión score matching? Planteo duda: Clasicamente el PSM se ha utilizado en un intento de homogeneizar cohortes de enfermos quienes han estado ?expuestos? a un tratamiento x Vs aquellos que no han estado expuestos (no expuestos). Esto aplica para medicamentos o procedimientos quirúrgicos o no. Bien, En algún articulo he leído que el PSM se puede

Hi there, I have data on earnings of 12000 individuals at two points in time. I intend to construct a transition matrix, where the typical element, p_ij, gives the probability that an individual ends at the j-th decile of the earnings distribution given that he was was initially at the i-th decile. Thus, this is a bi-stochastic matrix. The problem is that the income data is nearly discrete in the