[R] General Copula theory

Hi everyone! Firstly, let me specify that I an new to copula theory, so be gentle! I have two data sets containing wind data for 14 years, and I am to use Gumbel marginals and a Gumbel copula. The question is, how will I generate data from the marginals? I have 14 years of data (4 observations

[R] Lognormal AR(0,1) model

Hi everyone! I am trying to make two log-normal AR(0,1) model using R with a given correlation between them, \rho, on the form: X_t = \alpha X_{t-1} + a_t Y_t = \beta Y_{t-1} + b_t At the moment I have been making n values of correlated log-normal data, called a_t and b_t, and generated a starti

[R] Simulate from an ARIMA Model with fixed errors

Hi everyone!I am trying to make some synthetic data using two AR(1) models, but I am having some troubles.I want to make data from:x_t = \alpha x_{t-1} + a_{1t}y_t = \beta y_{t-1} + \gamma a_{1t} + \sqrt{1-\gamma^2} a_{2t}But I don't know how to set a fixed error term in the arima.sim() function...

Re: [R] Hide return values

Awesome, thanks! -Chris -- View this message in context: http://r.789695.n4.nabble.com/Hide-return-values-tp4680611p4680666.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailm

[R] Hide return values

Hi everyone! I am in the process of writing an R-package and while writing a summary function, I have come across a problem. I am able to print a summary table (as in a standard glm() summary) by using *cat()* but the values I return is also printet. How am I able to remove the return values from

[R] Extracting AICc and BIC from an ARIMA model.

Hi everyone! I am making some time series models, and as i want to compare a lot of models I thought it would be smart to compare the AIC, AICc and BIC values from the models. My question is, how can I extract the BIC and AICc from the model? As an example: kings <- scan("http://robjhyndman.com/

[R] Regression using ggplot2

Hi! I am currently working with a project where I want to plot the regression line in a plot using ggplot. The problem occurs when I want to add the second variable, i.e. the z in the source code: p = ggplot(data = dat, aes_string(x = "sd", y = "mean", z = "corr")) p = p + stat_smooth(method = l

Re: [R] regression imputation in R

Hi! For example if "data" is the complete dataset with both x and y values: tempdata = data[complete.cases(data[,1:2]),] # Regression data model = lm(y~x, data = tempdata) # Linear model >From this you can calculate the regression value of the missing values. Hope this helped! Reg

Re: [R] Adding additional points to ggplot2

That worked great! Best regards, Chris -- View this message in context: http://r.789695.n4.nabble.com/Adding-additional-points-to-ggplot2-tp4673928p4674059.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org maili

[R] Adding additional points to ggplot2

Hi! I am having a difficulty adding additional points to a plot using ggplot2.. The case is that I want to plot both original and estimated values in the same graph, and general I would use plot and then lines, but I do not know how to do it with ggplot... Thanks! Regards, Chris -- View this

Re: [R] R-squared and GLM

Haha, true true! ;) It was to be used as a measure on how good the models I use are, but I found out that the AIC would be much easier to implement, and as I understand, a better measure of how good the model fit. Thanks, Chris -- View this message in context: http://r.789695.n4.nabble.com/R-

[R] R-squared and GLM

Dear users, I want to compute r-squared values from a glm regression using a gamma distribution and an "identity" link-function, but find no such thing when using the summary() or names() function. My next guess was to calculate it by "hand", i.e. r2 = (sum((estimate - xbar)^2) /sum((x-xbar)^2))

[R] Finding parameters for residuals using GAMLSS and a lognormal dist.

Hi everyone! First of all: I am new to the forum, so please excuse my lack of knowledge on how to post a question... I am working on a project where I need to use the GAMLSS package, and the boss have asked me to try using the lognormal distribution. The regression goes as planned, but when eval