similar to: Generating groupings of ordered observations

Dear R users: When I create a table without Major Column headings, my *regular* column headings appear correct in the typeset latex file. The major row heading and row groups are as they should. w <- latex(mytab,title="",file="tab/my.tex",ctable=TRUE,caption="Descriptive statistics by

I am reading regressors from an excel file (I have no control over the file) and some of the element names have spaces: i.e. "Small Bank Aquired" but I have found that lm(SourceData ~ . - "Small Bank Aquired", mcReg) doesn't work (mcReg = modelCurrentRegressors) As they are toggles I have ran them through factor() to be treated propertly as 0 or 1 but due to the fact I

Dear R users I have been looking for functions that can deal with overdispersed poisson models. Some (one) of the observations are negative. According to actuarial literature (England & Verall, Stochastic Claims Reserving in General Insurance , Institute of Actiuaries 2002) this can be handled through the use of quasi likelihoods instead of normal likelihoods. The presence of negatives is not

Full_Name: David Sterling Version: 2.4.0 OS: OS X Submission from: (NULL) (64.81.102.199) lillie.test() dies without grace producing the error message: 'Error in if (pvalue > 0.1) { : missing value where TRUE/FALSE needed' when passed a vector of identical values. Examples: > lillie.test(c(0,0,0,0,0,0,0,0,0,0)) Error in if (pvalue > 0.1) { : missing value where TRUE/FALSE

Hi all, I wrote a r program as below: x <- 1:10 y <- c(3,3,3,3,3,3,3,3,3,3) fit <- lm(log(y) ~ x) summary(fit) And I expect to get some error message from R, because "y" is constant. But, I got the message as below: > summary(fit) Call: lm(formula = log(y) ~ x) Residuals: Min 1Q Median 3Q Max -6.802e-17 -3.933e-17 -1.063e-17 1.807e-17

i want to compare two variables (having numbers) serially for matching/dismatching both having equal length > x [1] 2 2 1 2 3 2 2 2 2 3 3 2 2 2 2 2 2 3 2 2 2 2 2 2 2 2 2 2 3 2 3 2 2 2 1 2 2 [38] 2 2 2 3 2 3 2 2 1 2 2 2 2 1 1 1 3 2 2 2 2 1 1 3 1 1 1 2 2 2 3 2 3 3 3 2 2 [75] 2 2 3 2 2 1 1 1 2 3 2 2 2 2 2 2 2 2 2 1 1 3 2 2 2 2 2 2 2 2 2 2 2 1 3 > y [1] 2 2 2 1 3 1 3 2 1 3 3 3 3 2 2 1 2 3

https://bugzilla.netfilter.org/bugzilla/show_bug.cgi?id=488 Summary: Chain/Groupings of networks don't total pkts and bytes correctly Product: iptables Version: 1.2.11 Platform: i386 OS/Version: RedHat Linux Status: NEW Severity: normal Priority: P2 Component: iptables

Quick question, as I attempt to learn R. For post-hoc tests 1) Is there an easy function that will take, say the results of tukeyHSD and create a grouping table. e.g., if I have treatments 1, 2, and 3, with 1 and 2 being statistically the same and 3 being different from both Group Treatment A 1 A 2 B 3 2) I've been stumbling over the proper syntax for simple effects for a tukeyHSD

Hello, I am trying to produce some graphics to visualize my data. I think I want histograms. I have a grouping variable that has 48 different groups. I would like to produce a graphic that contains three of of these groups in the same device (they are time steps). I would like create graphics for about 6 different variables (6 variables X 16 groupings of there = 96 graphics). I am unsure of how

https://bugzilla.netfilter.org/bugzilla/show_bug.cgi?id=488 netfilter@linuxace.com changed: What |Removed |Added ---------------------------------------------------------------------------- CC| |netfilter@linuxace.com ------- Additional Comments From netfilter@linuxace.com 2006-06-24 19:10 MET ------- Not

Hal, On 6/11/2012 12:48 PM, Andrew Trick wrote: > Ignoring compile time for a moment, I think an advantage of a DFA is modeling a situation where the hardware can assign resources to best fit the entire group rather then one instruction at a time. For example, if InstA requires either Unit0 or Unit1, and InstB requires Unit0, is {InstA, InstB} a valid group? Depending on your cpu, a DFA could

R community, I would like to know how to extract rows from a data frame (DF) such that each row in the new data frame (D.F) represents the first instance of a unique variable pairing in the original dataframe (ordered first by variable V1 then by variable V2). The unique function does not seem to be able to accomplish this. I imagine there must be a simple solution for this, but I can't

On Jun 11, 2012, at 12:07 PM, Hal Finkel <hfinkel at anl.gov> wrote: > Looking at VLIWPacketizerList::PacketizeMIs, it seems like the > instructions are first scheduled (via some external scheme?), and then > packetized 'in order'. Is that correct? Anshu? > In the PowerPC grouping scheme, resources are assigned on a group > basis (by the instruction dispatching

I'm trying to figure out how to use lmer to fit models with factors that have some nesting and some non-nested groupings. For example, in this paper: http://www.stat.columbia.edu/~gelman/research/published/parkgelmanbafumi.pdf we have a logistic regression of survey respondents' political preferences (1=Republican, 0=Democrat), regressing on sex, ethnicity, state (51 states within 5

Please forgive me, I feel exceptionally like a newbie. Although I've read screeds of documentation, I just can't see how this is done. I have a data frame that contains a number of pass/fails for certain variable sizes. From that, I would like to form another data frame that contains the proportions of pass/fails per variable. So, for example: df <- data.frame( Var=c(3,3,3,4,4),

Hi I needed some help with ANOVA I have a problem with My ANOVA analysis. I have a dataset with a known ANOVA p-value, however I can not seem to re-create it in R. I have created a list (zzzanova) which contains 1)Intensity Values 2)Group Number (6 Different Groups) 3)Sample Number (54 different samples) this is created by the script in Appendix 1 I then conduct ANOVA with the command >

Hi, I am new to R plot. I am trying to increase the data point observation when duplicate data points exist x y 1 10 1 10 2 3 4 5 9 8 in the about example 1, 10 would be displayed larger than the other data points. Could someone give me some assistance with this problem 757-864-7114 LARC/J.L.Shipman/jshipman Jeffery.L.Shipman at nasa.gov

On Jun 11, 2012, at 9:30 AM, Hal Finkel <hfinkel at anl.gov> wrote: > I'm considering writing more-detailed itineraries for some PowerPC CPUs > that use the 'traditional' instruction grouping scheme. In essence, > this means that multiple instructions will stall in some pipeline stage > until a complete group is formed, then all will continue. > > I expect to

I'm considering writing more-detailed itineraries for some PowerPC CPUs that use the 'traditional' instruction grouping scheme. In essence, this means that multiple instructions will stall in some pipeline stage until a complete group is formed, then all will continue. I expect to provide CPU-specific code to help determine when the currently-waiting instructions would form a group.

On Mon, 11 Jun 2012 10:48:18 -0700 Andrew Trick <atrick at apple.com> wrote: > On Jun 11, 2012, at 9:30 AM, Hal Finkel <hfinkel at anl.gov> wrote: > > > I'm considering writing more-detailed itineraries for some PowerPC > > CPUs that use the 'traditional' instruction grouping scheme. In > > essence, this means that multiple instructions will stall