similar to: ts startdate

Hi All, I have checked everything I could find abot graphics, but still cannot solve the problem. Are there any ways to make a graph that plots two lines and two different y-axes, each of them has a scale that is related to the respective line. For example, y1 has a range 1:50 and y1 ranges 0:1. The x-axe is the same for both. Thank you in advance. --- Gregor Gawron

Dear all, I am applying the StructTS function in ts-package. For some time series the program terminates and the following error appears: Error in optim(init[mask], getLike, method = "L-BFGS-B", lower = rep(0, : L-BFGS-B needs finite values of fn Do someone know what do I have to adjust in the original time series to avoid this error? It works fine for some subsets of the

Hi to all, First of all, I prefer to tell that I am a R-newbie, so I apologize if this is a silly question (I have tried looking in the manuals, but without luck). I have two variables, y and z, that I want to plot against x in the same plot. I have done this before, using points() after plot(). But now the problem is that y and z are in different units of measurement, and their ranges are very

i have: class Library << ActiveRecord::Base has_many :books end class Book << ActiveRecord::Base belongs_to :library end in my controller i have: render :xml=> Library.find(:all).to_xml(:include=>books) but, i would like put a condition in the books ( e.: pages >= 100 ) i would like to create a xml with all Libraries, but books with pages more than 100) How to

Dear R list: I modelled changes in a variable (mconc) over time (d) for individuals (replicate) given one of three treatments (treatment) using: mconc.lme <- lme(mconc~treatment*poly(d,2), random=~poly(d,2)|replicate, data=my.data) summary(mconc.lme) shows that the linear coefficient of one of the treatments is significantly different to zero, viz. Value Std.Error

Hello, I have a question on how to tabulate the time series data. I use RStudio, but if can be done in any other R editor, it should work in RStudio as well. > a1<-11:22 > a1ts<-ts(a1, frequency=4, start=c(1978,1)) > a1ts Qtr1 Qtr2 Qtr3 Qtr4 1978 11 12 13 14 1979 15 16 17 18 1980 19 20 21 22 If I click the variable "a1ts" on the

I am using semiparametric Model  library(mgcv) sm1=gam(y~x1+s(x2),family=binomial, f) How should I  find out standard error for ed50 for the above model ED50 =( -sm1$coef[1]-f(x2)) / sm1$coef [2]   f(x2) is estimated value for non parametric term.   Thanks [[alternative HTML version deleted]]

{all recent versions of R} Problem / design bug : diff.default() doesn't deal with "ts" objects properly, diff.ts() does, but that is only available from package "ts" where as the constructor function ts() is in base. It's not sufficient to just move diff.ts() to package base, since it relies itself on lag & lag.default which are also only in package ts.

On Thu, Aug 25, 2016 at 08:33:46AM +0100, Nux! wrote: > I've rebuilt libmateweather for EL7 with the aforementioned patch and it seems to have fixed the issue. > Feel free to use it until EPEL package the fix. > > http://li.nux.ro/download/nux//tmp/libmateweather7/ thanks Nux! I installed it and it now gets current conditions just fine. but I tried several different locations

I'm writing a program that will tell me whether I should wear a coat, so I'd like to be able to download daily weather forecasts and daily reports of recent past weather conditions. The NOAA has very promising tabular forecasts (http://forecast.weather.gov/MapClick.php?CityName=Ithaca&state=NY&site=BGM&textField1=42.4422&textField2=-76.5002&e=0&FcstType=digital),

Hi, recently I saw but did not pay too much attention to a question that concerned regression with positive coefficients. In Splus, thereis the nnls() function that can be used if I am not wrong, but what about R ? Now I have the same problem: doing a logistic regression under constraint that coefs are non negative. What can I do with R? is there a (weighted) nnls() counterpart available? Thanks

hello, I have a question about making n step ahead forecasts in cases where test and validation sets are availiable. For instance, I would like to make one step ahead forecasts on the WWWusage data so I hold out the last 10 observations as the validation set and fit an ARIMA model on the first 90 observations. I then use a for loop to sequentially add 9 of the holdout observations to make 1

I'm probably apporaching this all wrong to start but.... Suppose I have a monthly time series and I want to compute the mean of months 6,7, and 8. I want to plot the original time series and the seasonal time series, one above the other. When I do that as below the time series don't line up for reasons that are obvious. How can I change the base of the seasonal time series so I can make

Hello, My problem is, that I have to build hundreds of GARCH models to obtain volatility forecasts. I would like to run a loop, that would build those forecasts for me. There is no problem, with writing only the results of the forecasts, but I'd like to have stored results of the models in some file, that I could check later, what are the models like, to be able to compare if I should use

I am trying to download data from NASA web-service. I am using the following code; for( i in 1:8) { target1 <- paste0(" https://hydro1.gesdisc.eosdis.nasa.gov/daac-bin/access/timeseries.cgi?variable=NLDAS:NLDAS_FORA0125_H.002:TMP2m&location=GEOM:POINT( ", cities[i, "lon_nldas"], ",%20",

Hi. I am trying to follow this forecasting tutorial at: https://www.r-bloggers.com/basic-forecasting/ Using my own data, I cannot get past the first step, lots of laughs. dat3 <- structure(c(5973156.76, 5159011.20, 6695766.64, 6365359.00, 6495218.53, 7226302.39, 6835272.70, 7383501.57, 6962748.19, 7623278.72, 7274994.33 ,7919421.80, 7360740.81, 7436693.35,

i need to know how to estimate a linear regression whose coefficients sum to zero

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]]

Good morning everyone, I have attached an Excel file that contains a macro from which I call and use R's auto.arima function to generate forecasts. The program runs perfectly and it gets me the results; however, those results are pretty unusual. I also tried using the auto.arima function directly in the R console and still get weird results. The results are shown in columns AB, AC and AD

Hello, I have estimated a simultaneous equation model (similar to Klein's model) in R using the system.fit package. I have an identity equation, along with three other equations. Do you know how to explicitly identify the identity equation in R? I am also trying to forecast the dependent variables in the simultaneous equation model, while incorporating the identity equation in the