search for: least

I am running a Xen installation on a Centos-4.4 based test box, my desktop unit, and I am having intermittent problems installing certain pieces of software. Some time back I posted to this list regarding my inability to install Adobe Acrobat on this unit and was advised to essentially repackage the software and try again. This is beyond my present means of knowledge or time to acquire same and

..., ~cbc1+fruitveg4, dudleyls1rake.male,na.rm=TRUE, svytotal, keep.var=FALSE, keep.names=FALSE) cbc1 fruitveg4 statistic.agestrata18-24 statistic.agestrata25-34 statistic.agestrata35-44 statistic.agestrata45-54 1 Quintile 1 - Most deprived At least 5 portions a day 130.31565 535.3994 725.5864 464.61695 2 Quintile 2 At least 5 portions a day 116.25985 971.5924 1072.9432 1289.14396 3 Qui...

Hello R-helpers, I would like to calculate least square means after having built a GLM with quasipoisson errors. In my model the dependent variable is continuous, I have one continuous independent variable and one categorical independent variable (that is the variable for which I would like to calculate the least square means). I've looked...

Rick, Mark asked "why" you want the least amount of compression. I think we still do not understand your goals. If you can give us a hint at what you're trying to accomplish in your search for the least amount of compression, that might help us find the right answer. Brian Willoughby Sound Consulting On Jul 12, 2007, at 13:2...

I would really appreciate it if someone can give suggestions on how to do spectra fitting in R using ordinary least square fitting and non-negativity constraints. The lm() function works well for ordinary least square fitting, but how to specify non-negativity constraints? It wouldn't make sense if the fitting coefficients coming out as negative in absorption spectra deconvolution. Thanks. Xiuli

Friends, Is there a Partial Least Squares package implemented in R? Thanks, Lana [[alternative HTML version deleted]]

This is a simple problem, but a mystery to me. I'm trying to grab $Family "Scelionidae" from one dataframe and put it into another dataframe occupied with NA in $Family. The result is a "158" ends up there instead of Scelionidae. Simply put fam$Family[1] <- least$Family[1] If I have made a mistake here, can somebody point it out. I've included the simple steps I got there showing the structure and heads of the objects. ===== add a col of NA = Family > least$Family <- NA; str(least) 'data.frame': 243 obs. of 6 variables: $ sp :...

I'm wondering if english is not Rick's best language ("string setting" is just not quite the correct phrase). So, given that, I also wonder if by "least compression" he means "compressed into least number of bytes"??? If that is the case, then he actually wants "best compression" (most compression) or "flac --best" and his question makes perfect sense. Rick, I hope this helps and does not cause offense. - Larry...

Dear all, Does any one know if any R package or function can do Ordinary Least Products regression? Many thanks! Bill

...ffices where a keyboard and monitor(s) could then be connected. I want to run CentOS 7, later CentOS 8. The smaller, the better, however, there are certain key features I would like to have: - HDMI for 2 monitors - USB for keyboard - 2 extra USB for eg external harddisk etc. - both wifi and at least Gb Ethernet cable connector Probably at least 16 Gb of memory, capability to drive two high-resolution monitors and whatever else might be nice such as SSD of at least 256 Gb. Size wise it would be nice if it were no larger than a "book", whatever size that might be. Does anyone use so...

Hi, I know ways to do this but they all seem awkward and I somehow believe that there is a convenient shortcut. If I have a data.frame with many columns, how can I request all rows for which at least one column satisfy an expression? For instance, all rows where at least one column is negative. Many thanks, Werner

Dear all, I'm trying to select from a dataframe all rows which correspond to a factor (the id variable) for which there exists at least one positive value of a certain variable. As an example: x <- data.frame(matrix(c(rep(11,4),rep(12,3),rep(13,3),rep(0,3),1,rep(0,4),rep(1,2)),ncol=2)) > x X1 X2 1 11 0 2 11 0 3 11 0 4 11 1 5 12 0 6 12 0 7 12 0 8 13 0 9 13 1 10 13 1 and I want to select all rows pe...

...ne of those numbers. If ${EXTEN} is not equal to one of those numbers, I'd like to send the call out to a PRI group, regardless of dialed sequence length or pattern. It seems I cannot do this with *'s pattern matching, due to the order in which extensions are parsed, which seems to be least-specific to most-specific. This causes all kinds of headaches when trying to use wildcards, since wildcards are super-least-specific. My desire would be to have the more specific matches done first, so that if ${EXTEN} would be matched in an order that makes sense. I understand why matching...

What fun. I don't often stoke up the boiler and actually compile open-source code, but here I am at the beginning of just such a joyous and wondrous adventure. I'm running the latest level of AIX (V5.3...V4.3 has been obsolete for at least, what, 5 years) and using the IBM compiler (xlc is similarly obsolete, from back when the compiler came with the O/S...oh, for the halcyon days of Unix's youth) as above The IBM compiler is now know as xlc rather than xlC, and configure doesn't find it: checking for xlC_r... no checkin...

Greetings, I would like to fit a multiple linear regression model in which the residuals are expected to follow a multivariate normal distribution, using weighted least squares. I know that the data in question have biases that would result in correlated residuals, and I have a means for quantifying those biases as a covariance matrix. I cannot, unfortunately, correct the data for these biases. It seems that this should be a straightforward task, but so much of...

I need to find out the difference between the way R calculates weighted regression and standard regression. I want to plot a 95% confidence interval around an estimte i got from least squares regression. I cant find he documentation for this ive looked in ?stats ?lm ?predict.lm ?weights ?residuals.lm Can anyone shed light? thanks Chris. -- View this message in context: http://n4.nabble.com/weighted-least-squares-vs-linear-regression-tp1387957p1387957.html Sent from the...

Dear all, When doing nonlinear regression, we normally use nls if e are iid normal. i learned that if the form of the variance of e is not completely known, we can use the IRWLS (Iteratively Reweighted Least Squares ) algorithm: for example, var e*i =*g0+g1*x*1 1. Start with *w**i = *1 2. Use least squares to estimate b. 3. Use the residuals to estimate g, perhaps by regressing e^2 on *x*. 4. Recompute the weights and goto 2. Continue until convergence i was wondering whether there is a instruc...

...a = EM4) F is a 4-level factor, the rest are covariates centered at their mean (Y is a two-column matrix). I have tried to find functions to give the model-adjusted means (adjusted at the covariates'means) and their standard deviations for each. (That is, what I believe is called in SAS "least square or LS-means, whose errors one obtains by STDERR) I have tried help.search and RSiteSearch with several terms including "standard errors", "least square means", "adjusted means". I have found how to extract the SE from coefficients (se.coef from package arm),...

Hi, am very new to R and I've written an optim function, but can't get it to work least.squares.fitter<-function(start.params,gr,low.constraints,high.constraints,model.one.stepper,data,scale,ploton=F) { result<-optim(par=start.params,method=c('Nelder-Mead'),fn=least.squares.fit,lower=low.constraints,upper=high.constraints,data=data,scale=scale,ploton=ploton) retur...

...imple problem, but a mystery to me. > I'm trying to grab $Family "Scelionidae" from one dataframe and put it into > another dataframe occupied with NA in $Family. The result is a "158" ends > up there instead of Scelionidae. > Simply put fam$Family[1] <- least$Family[1] > > If I have made a mistake here, can somebody point it out. I've included > the simple steps I got there showing the structure and heads of the objects. > ===== add a col of NA = Family >> least$Family <- NA; str(least) > 'data.frame': 243 obs....