search for: unemploy

Hey all, first time poster here. I'm new to R and working on my first real programming and forecasting asignment. I'm using unemployment data from 1948-2012. I successfully completed part a and the linear fit for part b, but i am really struggling fitting a polynomial with a power greater than 2 to my forecast. I'll upload my R code at the bottom. Any help is very much appreciated! Thank You! (a) Produce a time-series plot...

Dear r-devel list members, On a couple of occasions I've encountered the issue illustrated by the following examples: --------- snip ----------- > mod.1 <- lm(Employed ~ GNP.deflator + GNP + Unemployed + + Armed.Forces + Population + Year, data=longley) > mod.2 <- update(mod.1, . ~ . - Year + Year) > all.equal(mod.1, mod.2) [1] TRUE > > f <- function(mod){ + subs <- 1:10 + update(mod, subset=subs) + } > f(mod.1) Call: lm(formula = Employed ~...

...rstand there might be a place here to do some sort of mixed model, but I would prefer to present a "correlation", and am not sure how to extract such an output from a mixed model. Also, here is a short dummy code to give an idea of what I am talking about: attach(longley) N <- length(Unemployed) block <- c( rep( "a", N), rep( "b", N), rep( "c", N) ) Unemployed.3 <- c(Unemployed + rnorm(1), Unemployed + rnorm(1), Unemployed + rnorm(1)) GNP.deflator.3 <- c(GNP.deflator + rnorm(1), GNP.deflator + rnorm(1), GNP.deflator + rnorm(1)) cor(Unemployed,...

...e reproducible code.] I'm doing a multivariate bootstrap, using boot::boot(), where the output of the basic computation is a k x p matrix of coefficients, representing a tuning constant x variable, as shown in the $t0 component from my run, giving a 3 x 6 matrix > lboot$t0 GNP Unemployed Armed.Forces Population Year GNP.deflator 0.00 -3.4472 -1.828 -0.6962 -0.34420 8.432 0.15738 0.01 -0.1798 -1.361 -0.5881 -1.00317 5.656 -0.02612 0.08 1.0907 -1.086 -0.4583 -0.08596 2.642 0.57025 > ?boot doesn't say how these are strung out...

...ash} & #{t.name} is on bkmk #{b.name}" end end end ...results in this output: hash is 195=>1 (80s is on bkmk 80s Video Clips) hash is 195=>1 (culture is on bkmk 80s Video Clips) hash is 195=>1 (music is on bkmk 80s Video Clips) hash is 195=>1,196=>1 (activism is on bkmk Unemployment: A National Obligation) hash is 195=>1,196=>1 (careers is on bkmk Unemployment: A National Obligation) hash is 195=>1,196=>1 (eonomics is on bkmk Unemployment: A National Obligation) hash is 195=>1,196=>1 (politics is on bkmk Unemployment: A National Obligation) hash i...

In Germany the Unemployment Agency uses a sectioning of the german map that is different from the usual Administrative Boundaries. Some demographic data are available in Administrative Boundaries only, some in Unemployment Boundaries only. I would like to generate estimates in one boundary system of data availabe in the...

Dear All, I would like to ask if it is possible to estimate a hazard function using the muhaz command when all the data is right-censored. My data has information of the number of weeks people has been unemployed but all of them are unemployed at the date of the survey, that is, I cannot observed when the individuals leave the unemployment state. I appreciate your help, Best, Monica L.

...0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1) f<-structure(list(c("GDP (LCU,bn)", "GDP ($, bn)", "GDP per capita (LCU)", "Ratio to EZ GDP Per Cap", "Share of World GDP (Intl $, %)", "Real GDP Growth (%)", "Population (mn)", "Unemployment Rate (%)", "Ratio of Employed/Unemployed", "PPP Exchange Rate", "Nominal Exchange Rate (LCU per $)", "Inflation (%)", "Main Lending Rate to Private Sector (%)", "Claims on Central Gov", "Claims on Private Sector", "...

...lm.ridge(Employed ~ .,longley,lambda = seq(0,0.1,0.001)) > plot(gr) > select(gr) modified HKB estimator is 0.004275 modified L-W estimator is 0.0323 smallest value of GCV at 0.003 > ##let's choose 0.03 for lambda > coef(gr)[gr$lam == 0.03,] GNP.deflator GNP Unemployed Armed.Forces Population Year -1620.429355 0.021060 0.007994 -0.013146 -0.007752 -0.101880 0.869116 But how does one obtain the customary 'lm' summary information for the model above? I tried supplying the chosen lambda to Design::ols() using its 'penalty...

Hello, I have the following problem. I am running simulations on possible states of a set of agents (1=employed, 0=unemployed). I store these simulated time series in a matrix like the following, where rows indicates time periods, columns the number of agents (4 agents and 8 periods in this case): Atr=[ 1 1 1 1 1 1 0 1 1 1 0 1 1 1 0 1 0 1 0 1 0 1 0 1 0 1 0...

On Wed, Feb 16, 2011 at 3:46 PM, John R. Dennison <jrd at gerdesas.com> wrote: > ? ? ? ?issue? ?I don't get it. ?You seem to think that money is the end > ? ? ? ?all be all for OSS. ?I would suggest that's a mindset you may > ? ? ? ?wish to change as money doesn't drive OSS. Are you saying there are no OSS folks who have lost their houses, their cars and their Internet

...print the value to see what objects were saved. print(load(con)) close(con) col <- c("black", rainbow(5, start=.6, end=.1)) clr <- col[c(1,3,6)] contour(dest0$x1, dest0$x2, dest0$fhat, nlevels=4, xlim=c(-8,4), ylim=c(-3,0), cex.lab=1.25, xlab="GNP", ylab="Unemployed" ) contour(dest1$x1, dest1$x2, dest1$fhat, nlevels=4, add=TRUE, col=clr[2]) contour(dest2$x1, dest2$x2, dest2$fhat, nlevels=4, add=TRUE, col=clr[3]) lines(rbind(cm0, cm1, cm2)) points(rbind(cm0, cm1, cm2), col=clr, pch=16, cex=1.5) I've tried filled.contour(), as below, except that...

...ox equal to Ridge$Coef[near value of kHKV] and it does not seem to happen, why? Values: > Ridge$kHKB [1] 0.004275357 Using the calculation above (third question, third point): Coef= [,1] 1 -0.095492310 GNP.deflator -0.052759002 GNP 0.070993540 Unemployed -0.004244391 Armed.Forces -0.005725582 Population -0.413341544 Year 0.048420107 And if I take from Ridge&coef: Ridge$coef[0.004] GNP.deflator -0.03098507 GNP -1.32553151 Unemployed -1.53237769 Armed.Forces -0.63334911 Population -0.88690241 Year 6.82105049 Any help, sugg...

...creen with multiple plots in it. Something like the example below. When I save that with ggsave(), only the last plot gets saved (pPath in the example) instead of the entire figure. Any suggestions how I can save this kind of figures automated? Thanks, Thierry library(ggplot2) pPoint <- qplot(unemploy/pop, psavert, data=economics) pPath <- qplot(unemploy/pop, psavert, data=economics, geom="path") grid.newpage() pushViewport(viewport(layout = grid.layout(2, 1))) print(pPoint, vp = viewport(layout.pos.row = 1, layout.pos.col = 1)) print(pPath, vp = viewport(layout.pos.row = 2, layout....

...staller_1.4.3 [13] ctv_0.7-4 sos_1.3-1 [15] brew_1.0-6 Hmisc_3.9-3 [17] survival_2.36-12 MASS_7.3-17 loaded via a namespace (and not attached): [1] cluster_1.14.2 digest_0.5.2 tools_2.15.0 # copy and paste the following: library( catdata ) data( unemployment ) unempt <- unemployment unempt$durbin <- unempt$durbin - 1 library( reshape ) unempt <- melt( table( unempt ) ) unempw <- cast( unempt, age ~ durbin ) names( unempw ) <- c( 'age', 'short', 'long' ) modt <- glm( durbin ~ age, weights = value, family =...

Dear list, I get some strange results with daply from the plyr package. In the example below, the average age per municipality for employed en unemployed is calculated. If I do this using tapply (see code below) I get the following result: no yes A NA 36.94931 B 51.22505 34.24887 C 48.05759 51.00198 If I do this using daply: municipality no yes A 36.94931 48.05759 B 51.22505 51.00198...

...ed. Firstly, sharing experience and getting more people interested in mentoring will help. Secondly, asking the participating (ex-) students can give us better understanding of the daily issues they have/had. Lastly, potentially involving HR people could help to transition our best students (or unemployed contributors) to more stable positions and thus keeping them around longer. We have thought of a several potential directions for this BoF: * Discuss how to make contributions to llvm easier. Eg. classify the bugs/fixmes for newbies and put them online... * Share mentoring experienc...

...It is just meant to show the structure of the dataset. The variables of interest are p_0, ... p_37. They represent types of activity of the 6021 persons interviewed in 38 consecutive period. The values for p_0 and p_37 are coded as follows: 1 = self-employed 2 = employed 3 = in training 4 = unemployed NA = no information available p_0 is the period before p_1. This period was just before the survey, so that none of the individuals were interviewed in this period. p_37 is the period after p_36. This period was just after the survey, so that none of the individuals were interviewed in this...

...vfit function. My historical data set is a pool of loans with monthly observed default status for the next 24 months. The data is left truncated (delayed entry to observation window after the loan is opened) and right censored. I would like to fit the model with time varying covariate such as unemployment rates and time constant variables at loan application, and then use the model to predict the probability of default in the next 24 month for the pool of loans we have right now, by using function survfit. When loans are outside of the observed time window, is it reliable to use survfit func...

We would like to load data from Statistics Canada (http://www.statcan.gc.ca/) using R, for example, Employment and unemployment rates. It seems to me that the tables are displayed in HTML. I was wondering if you know how to load these tables. Thanks, -james