similar to: Loop with string variable AND customizable "summary" output

I am relatively new to R and object oriented programming. I have relied on SAS for most of my data analysis. I teach an introductory undergraduate forecasting course using the Diebold text and I am considering using R in addition to SAS and Eviews in the course. I work primarily with univariate or multivariate time series data. I am having a great deal of difficulty understanding and working with

Dear all I have a work-flow issue with lm(). When I use > lm(y1~x1, anscombe) Call: lm(formula = y1 ~ x1, data = anscombe) Coefficients: (Intercept) x1 3.0001 0.5001 I get as expected the formula, "y1 ~ x1", in the print()ed results or summary(). However, if I pass through a formula object > (form <- formula(y1~x1)) y1 ~ x1 > lm(form, anscombe) Call:

moments::anscombe.test(x) does give errors when x has too few values or if all the values in x are the same > moments::anscombe.test(c(1,2,6)) Error in if (pval > 1) pval <- 2 - pval : missing value where TRUE/FALSE needed > moments::anscombe.test(c(2,2,2,2,2,2,2,2)) Error in if (pval > 1) pval <- 2 - pval : missing value where TRUE/FALSE needed You can use tryCatch() to

Hi all, While running the anscombe.test in R, I'm getting an error of *Error in if (pval > 1) pval <- 2 - pval : missing value where TRUE/FALSE needed* for a few time series columns whereas for most of the series the function is working fine. I have checked for those specific columns for missing values. However, there is no NA/NAN value in the dataset. I have also run kurtosis for

Hi Bill, Thanks for prompt reply and letting me know a way around it. I have more than 1200 observations and not all the values are the same. However, my data points are quite similar, for example, 0.079275, 0.078867, 0.070716 in millions and etc. I have run the data without converting it to millions and I still get the same error message. As I have kurtosis value, it should be fine for the

I have an array with 44800 columns and 24 rows I would like to compute the row average for the array 100 columns at a time, so I would like to end up with an array of 24 rows x 448 columns. I have tried using apply(dataset, 1, function(x) mean(x[])), but I am not sure how to get it to take the average 100 columns at a time. Any ideas would be welcomed. thanks, Spencer [[alternative HTML

Hi, How to mark points on x axis of a graph keeping x axis as constant and changing y from y1 to y2 respectively. I want to highlight the area from y1 to y2. Any suggestions Thank you Jeet [[alternative HTML version deleted]]

I don't have much experience with r. What I am trying to do is to turn regression coefficients (after I run a lm or glm model) into some matrix such that I can do some post-estimation calculation, for example predicted probabilities in glm model, etc.. Or, is there any function in r that I can use to do something along that line? thanks. Jun Xu, Ph.D. Department of Sociology Ball State

useRs, I have a data frame where four of the columns of the data frame represent the values of a two-by-two matrix. I'd like to, row-by-row, go through the data frame and use the four columns, in matrix form, to perform calculations necessary to create new values for variables in the data frame. My first idea was to use apply: apply(as.array(data.frame[,1:4]), 1, matrix, nrow=2) Though

I have a question about the D'Agostino skewness test and the Anscombe-Glynn kurtosis test. agostino.test(x, alternative = c("two.sided", "less", "greater")) anscombe.test(x, alternative = c("two.sided", "less", "greater")) The option "alternative" in those two functions seems to be the null hypothesis. In the output, the

Hi All, I'm using the subset function to select a list of variables, some of which are contiguous in the data frame, and others of which are not. It works fine when I use the form: subset(mydata,select=c(x1,x3:x5,x7) ) In reality, my list is far more complex. So I would like to store it in a variable to substitute in for c(x1,x3:x5,x7) but cannot get it to work. That use of the c function

Another bad case is > moments::anscombe.test(rep(c(1,1.1),length=35)) Error in if (pval > 1) pval <- 2 - pval : missing value where TRUE/FALSE needed I haven't checked the formulas carefully, but I suspect the problem is from taking the cube root of a negative number in z <- (1 - 2/(9 * a) - ((1 - 2/a)/(1 + xx * sqrt(2/(a - 4))))^(1/3))/sqrt(2/(9 * a)) In R, the

We're in the process of migrating from mbox over to maildir. I'm running into a problem with the proxy and timeouts. Appears the idle timeout is set to 60 seconds. This is a bit too low for some of our large mbox files :( Any plans on adding the: #define CLIENT_LOGIN_IDLE_TIMEOUT 60 #define AUTH_REQUEST_TIMEOUT to the .conf file to be tunable on the fly? I ended up just patching the

Hi, I would like to create a plot of y1,y2,y3,y4 against x for several subjects such that y1 and y2 are plotted against x in one panel and y3 and y4 against x in another panel. Thus if there are 3 subjects I should end up with 6 panels. Is there a simple way of doing so (i.e. without calling xyplot() several times, and then padding the results together)?? Regards S?ren

On Wed, Apr 22, 2020 at 08:03:29AM +0200, Christoph Hellwig wrote: > > > On Tue, Apr 21, 2020 at 09:21:46PM -0300, Jason Gunthorpe wrote: > > +void nouveau_hmm_convert_pfn(struct nouveau_drm *drm, struct hmm_range *range, > > + u64 *ioctl_addr) > > { > > unsigned long i, npages; > > > > + /* > > + * The ioctl_addr prepared here is

https://bugzilla.samba.org/show_bug.cgi?id=5071 Summary: Enhancement Request - Customizable Connection Timeout Option Product: rsync Version: 2.6.9 Platform: Other OS/Version: Other Status: NEW Severity: enhancement Priority: P3 Component: core AssignedTo: wayned@samba.org

On 5/1/20 11:20 AM, Jason Gunthorpe wrote: > From: Jason Gunthorpe <jgg at mellanox.com> > > Presumably the intent here was that hmm_range_fault() could put the data > into some HW specific format and thus avoid some work. However, nothing > actually does that, and it isn't clear how anything actually could do that > as hmm_range_fault() provides CPU addresses which

Hello! I'm a newcomer to R hoping to replace some convoluted database code with an R script. Unfortunately, I haven't been able to figure out how to implement the following logic. Essentially, we have a database of transactions that are coded with a geographic locale and a type. These are being loaded into a data.frame with named variables city, type, and price. E.g., trans$city

Dear R Users: I'm a STATA user converting to R, and I'd like to be to do the following. #Assign var_1 and var_2 a value 10->var1 20->var2 #Now I'd like to print the values of var_1 and var_2 by looping through var_1 and var_2 in such a manner: while(y<3){ print(var_y) y+1->y } In STATA, the "y" appended to " var_" is called the local variable and

Hello there everybody! Terrific... a mailing-list for compiz with David on board! Ok, I started off with writing some functions using cairo to draw me the needed elements for drop-shadows (atm stand-alone to focus on the proper generation of the shadow-parts) and currently still fiddle with the tweakable parameters. Right now I have... shadow-radius (e.g. 20 pixels) 2D-offset vector (e.g. 10