similar to: Time Series - Trend Line

Is there a way to access the numeric results (standard deviation and correlation) obtained with the taylor.diagram ? -- View this message in context: http://r.789695.n4.nabble.com/taylor-diagram-from-plotrix-package-tp4545669p4545669.html Sent from the R help mailing list archive at Nabble.com.

Hello everyone, I was looking for a way to classify time-series based on the curve-fit. I try to campute several trends so i was thinking to link each trend with a function. increase with exponential for example, increase and decrease with a gaussian etc. The possiblities are endless though and it seems that is not always working well, especially if you work on small time-series (of 5-10 points

I've seen some questions regarding the output of multiple objects from a function, however the suggestions all end up suggesting the use of return(list(result1=result1, result2=result2 , result3=result3)). How can I return multiple objects that are 2 big to be added to a list? -- View this message in context:

I got a set of data which has seasonal trend in form of sinx, cosx, I don't have any idea on how to deal with it. Can you give me a starting point? Thanks, Terry

Hello, I am analyzing some climate time series data using the Mann Kendall package and was wondering if there was a way to calculate the trend using Sen's nonparametric estimator slope in R? Thank you in advance, Barry _________________________ Barry Baker, Ph.D. Global Climate Change Initiative The Nature Conservancy 2424 Spruce St., Suite 100 Boulder, CO 80302 Tel: (303)-541-0322 Fax:

Dear list users How is it possible to visualise both a linear trend line and a quadratic trend line on a plot of two variables? Here my almost working exsample. data(Duncan) attach(Duncan) plot(prestige ~ income) abline(lm(prestige ~ income), col=2, lwd=2) Now I would like to add yet another trend line, but this time a quadratic one. So I have two trend lines. One linear trend line

(My apologies if this is a repeated posting. I couldn't find any trace of my previous attempt in the archive.) I'm having trouble with forecast() in the dse2 package. It works fine for me on a model without a trend, but gives me NaN output for the forecast values when using a model with a trend. An example: # Set inputs and outputs for the ARMA model fit and test periods

Hi, I have a time series (say "x") of 13 years showing an evident increase. I want to exclude two observations (the fourth and 10th), so I do: > trend.test(x[-c(4,10)]) where: > x[-c(4,10)] [1] 7 37 79 72 197 385 636 705 700 1500 1900 and I get: Spearman's rank correlation rho data: x[-c(4, 10)] and time(x[-c(4, 10)]) S = 4, p-value < 2.2e-16

Hi, I have a time series (say "x") of 13 years showing an evident increase. I want to exclude two observations (the fourth and 10th), so I do: > trend.test(x[-c(4,10)]) where: > x[-c(4,10)] [1] 7 37 79 72 197 385 636 705 700 1500 1900 and I get: Spearman's rank correlation rho data: x[-c(4, 10)] and time(x[-c(4, 10)]) S = 4, p-value < 2.2e-16

When I make a sample in sp, for example a random samping of 5 points in dataset1: sample.dataset1=spsample(dataset1, n = 5, "random") I have a sp object for the selected sampling... My question is : How can I extract from dataset2 the points & data for the coordinates(sample.dataset1) ? The dataset2 would be an object with the same area and coordinate system, but I would like to

Dear r-help, I would like to use the 'ppm' function of the 'spatstat' package to fit a Strauss inhibition model. I understand that I can specify a parametric model for the "background" trend, but how would I specify a trend which is estimated using a Kernel density smoother? In particular, I would like to use the 'kde' function of the 'ks' package to

R has a Dickey-Fuller Test implementation (adf.test) that tests for unit roots in an autoregressive process with a constant and linear trend. Is there a DF implementation that doesn't use the constant or trend? Thanks, Jake. -- View this message in context: http://www.nabble.com/Dickey-Fuller-Tests-with-no-constant-and-no-trend-tp23565210p23565210.html Sent from the R help mailing list

I have been trying to simulate from a time series with trend but I don't see how to include the trend in the arima.sim() call. The following code illustrates the problem: # Begin demonstration program x <- c(0.168766559, 0.186874000, 0.156710548, 0.151809531, 0.144638812, 0.142106888, 0.140961714, 0.134054659, 0.138722419, 0.134037018, 0.122829846, 0.120188714,

Hello R community, I would like to test for learning effects by subjects in my experiment. Each subject participates in six consecutive auction rounds of the same treatment. The response variable is the efficiency of an auction outcome measured by a real number. Since the efficiency increases over the six rounds, I suppose that subjects learn about the rules of the auction institution, but I

Dear All, My question is: how can I estimate VECM system with "unrestricted trend" (aka "case 5") option as a deterministic term? As far as I know, ca.jo in urca package allows for "restricted trend" only [vecm <- ca.jo(data, type = "trace"/"eigen", ecdet = "trend", K = n, spec = "transitory"/"longrun")].

Dear sir, I am Shibu John from Thrombosis Research Institute India. It is a multidisciplinary organisation concerned with the interrelated problems of thrombosis and atherosclerosis. I was searching for Cochran armitage trend test program in R. Then I had seen your R coding for C-A trend test. I tried that in the R software. But I can?t run the program due the [Error: could not find function

Dear all, I have several response variables estimated from some simulations, and I would like to identify the thresholds for trend changes. Fro example, below I forced two different response behaviours and on x is time unit. x<-1:1500 y<-x/exp(x^0.2) smaller15<-y[y<15] y<-ifelse(y<15,y+rnorm(length(smaller15)), 15+rnorm(1000-length(smaller15), 0, 0.9))

Hello, is there a R package that provides a log rank trend test for survival data in >=3 treatment groups? Or are there any comparable trend tests for survival data in R? Thanks a lot Markus -- Dipl. Inf. Markus Kreuz Universitaet Leipzig Institut fuer medizinische Informatik, Statistik und Epidemiologie (IMISE) Haertelstr. 16-18 D-04107 Leipzig Tel. +49 341 97 16 276 Fax. +49 341 97 16

I would like to compare the incidence rates of three groups. They are supposed to have different risks so I would like to test whether there is a increasing trend in the incidence rates. Does R or any packages provide a trend test for incidence rates? I checked epiR and epitools. It seems they do not have this function. Thank you for the help. -- View this message in context:

Hi All: I was looking for, but could not locate in the packages, or in the R archive searches if there exists an R implementation of Cuzick's test of trend. The test is described as follows: An extension of the Wilcoxon rank-sum test is developed to handle the situation in which a variable is measured for individuals in three or more (ordered) groups and a non-parametric test for trend