similar to: regression using a lagged dependent variable as explanatory variable

Hi, I would like to count the columns of a data.frame. I know how to count the rows, but not the columns. Can someone tell me how to do it? My best regards, Giacomo Moro --------------------------------- [[alternative HTML version deleted]]

Hi, I would like to use R to estimate the following model: X(t) = a + b1*X(t-1) + b2*X(t-2) + c1*Y(t) + c2*Y(t-1) + c3*Y(t-2) Is there any R function that performs this type of estimation? I know that if I only have one time series (i.e. lagged value of X) on the right hand side then there are R functions to do the estimation. I am thinking a work around by preparing X(t-1), X(t-2),Y(t),Y(t-1)

hi guys, i have some trouble in creating lagged variables to use as external regressors. i'm trying to use lag(x) but it gives me as result the same time series (x), adding this part at the end: attr(,"tsp") [1] 0 2323 1 where do i wrong?are there other functions to be used? thanks sara -- View this message in context:

Hi guys, I am afraid I am stuck with an estimation problem. I have two variables, X and Y. Y is explained by the weighted sum of n lagged values of X. My aim is to estimate the two parameters c(alpha0,alpha1) in: Yt = Sum from j=1 to n of ( ( alpha0 + alpha1 * j ) * Xt-j ) Where Xt-j denotes the jth lag of X. I came up with this approach because I thought it would be a good idea to estimate

Hi, How do I can make a lagged scatterplot of two variables: Yt (nao) versus Xt-h (mei) if they have the following structure: >series mei nao Jan 1950 -1.036 0.55 Feb 1950 -1.133 3.31 Mar 1950 -1.259 0.81 Apr 1950 -1.027 1.60 May 1950 -1.399 -1.73 Jun 1950 -1.366 1.26 Jul 1950 -1.300 -0.87 . . . I've tried with lag.plot but I don't understanf how to use it Thanks in

Hi, I was wondering why the results from lm and dynlm are not the same for what I think is the same model. I have just modified example 4.2 from the Pfaff book, please see below for the code and results. Can anyone tell my what I am doing wrongly? Many thanks, Werner set.seed(123456) e1 <- rnorm(100) e2 <- rnorm(100) y1 <- ts(cumsum(e1)) y2 <- ts(0.6*y1 + e2) lr.reg <- lm(y2

Simple usage questions that I ought to be able to figure on my own, but can't. 1.I'm able to produce a cross tabulation table showing counts with either table or xtabs. But I want column percentages for interpretation, and it seems stupid to sit there with a calculator figuring marginals and column percentages. How to make R do it after this: > x <- c(1,3,1,3,1,3,1,3,4,4)

I'm currently working with some time series data with the xts package, and would like to generate a forecast 12 periods into the future. There are limited observations, so I am unable to use an ARIMA model for the forecast. Here's the regression setup, after converting everything from zoo objects to vectors. hire.total.lag1 <- lag(hire.total, lag=-1, na.pad=TRUE) lm.model <-

Hi, How to unlist list column value and add column into data frame. Data frame ID ContractDe PassengersDe TrainnerDe 1 list(ConID=c("Zx","78yu"),ConRes = c("98","Tut")) list(PassID

Is it possible to fit a lagged regression, "y[t]=b0+b1*x[t-1]+e", using the function "lag"? If so, how? If not, of what use is the function "lag"? I get the same answer from y~x as y~lag(x), whether using lm or arima. I found it using y~c(NA, x[-length(x)])). Consider the following: > set.seed(1) > x <- rep(c(rep(0, 4), 9), len=9) > y <-

Dear all, I am having difficulties using the seemingly-simple function lag. I have a dataframe with several weather variables (maxitemp, windspeed, rainfall etc), and the response variable (admissions). The dataset is fairly large (1530 observations). I simply want to model the response against a lag of a couple of the explanatory variables, say maxitemp and rainfall. I would like to look at

All: How do I obtain one step ahead out-of-sample forecasts from a model using "dyn" or "dynlm" ? Thanks! Best, John [[alternative HTML version deleted]]

Hello I'm very new to R (which is excellent), so apologies if this has already been raised. In the spdep package, I'm trying to undertake an autoregressive mixed model using the lagsarlm function. This is working fine, but there does not appear to be a method of including an explanatory variable without it automatically being included as a lagged term. I'm after something along the

Hi all, I've just started working my way through Mike West and Jeff Harrison's _Bayesian Forecasting and Dynamic Models_, and I was wondering if there were any publically-available packages to handle dynamic linear models, as they describe. I found the "dynlm" package, but either I don't yet understand what's going on or that package uses a different sense of the phrase

Hello, I am looking for some help with this question: how could I test structural breaks in a instrumental variables´s model? For example, I was trying to do something with my model with three time series. tax_ivreg <- ivreg(l_y ~ l_x2 + l_x1+ dl_y | lag(l_x2, -1)+lag(l_x2, -2)+ lag(l_x1, -1)+lag(l_x1, -2)+lag(l_y, -1)+lag(l_y, -2), data=tax1) summary(tax_ivreg) ## after estimating it,

I want to set up a model with a formula and then run dynlm(formula) because I ultimately want to loop over a set of formulas (see end of post) R> form <- gas~price R> dynlm(form) Time series regression with "ts" data: Start = 1959(1), End = 1990(4) <snip> Works OK without a Lag term R> dynlm(gas ~ L(gas,1)) Time series regression with "ts" data: Start =

? To whoever it may correspond, My name is Oscar Saenz and I am working on my thesis in Spain. I am using GAMs in "R" and, now that I have estimated my models, I need to plot the predicted smooth functions against the dependent variable (just as in Carlslaw et al. 2007, fig. 1*). Otherwise, I'd like to know how to plot the smoothed predictor variable values against the partial

Thanks, Also, every method inherited by LoopBase causes the same error, while Loop methods go smooth. On 9 May 2013 01:05, Andrew Trick <atrick at apple.com> wrote: > > On May 8, 2013, at 7:43 PM, Giacomo Tagliabue <giacomo.tag at gmail.com> > wrote: > > Hello, > I am building a loop pass following these instructions: >

Each of the data sets contains monthly observations on price indices for 7 countries. I use the fitted values from reg1 in the reg2 model. The interior loop executes without error as long as I explicitly specify the data set, i.e. data=dat70. However the code fails to execute if I specify the model in the form of the commented line, i. e reg1 <-dynlm(form1,data=Dnames[j]) I get the following

Wow, commenting those two lines worked out fine for me, thanks! On 9 May 2013 09:34, Giacomo Tagliabue <giacomo.tag at gmail.com> wrote: > Thanks, > Also, every method inherited by LoopBase causes the same error, while Loop > methods go smooth. > > > On 9 May 2013 01:05, Andrew Trick <atrick at apple.com> wrote: > >> >> On May 8, 2013, at 7:43 PM,