search for: nterm

...ezverk at cisco.com According to documentation ` tcp sport { 12345-54321 }` should be supported but it fails with Segmentation Fault. See debug below: sudo nft --debug all add rule ip ipv4table ipv4chain-1 tcp sport { 12345-54321 } Entering state 0 Reducing stack by rule 1 (line 747): -> $$ = nterm input (: ) Stack now 0 Entering state 1 Reading a token: --accepting rule at line 275 ("add") Next token is token "add" (: ) Shifting token "add" (: ) Entering state 19 Reading a token: --accepting rule at line 631 (" ") --accepting rule at line 249 ("ru...

...lists the following line: table ip test { chain input { meta priority :0034 } } And, It's impissible use this: sudo nft --debug=all add rule ip test input meta priority :10 Stack now 0 1 15 10 44 Entering state 213 Next token is token "colon" (: ) Error: popping nterm expr (: ) Stack now 0 1 15 10 44 Error: popping nterm ruleid_spec (: ) Stack now 0 1 15 10 Error: popping token "rule" (: ) Stack now 0 1 15 Error: popping token "add" (: ) Stack now 0 1 Shifting token error (: ) Entering state 3 Next token is token "colon" (: ) Error:...

...9 0.2884918 [8] 0.4327377 0.5769836 Here is the corrected code: if (type=="terms"){ asgn <- attrassign(object) beta<-coef(object) hasintercept<-attr(tt,"intercept")>0 if (hasintercept) asgn$"(Intercept)"<-NULL nterms<-length(asgn) predictor<-matrix(ncol=nterms,nrow=NROW(X)) dimnames(predictor)<-list(rownames(X),names(asgn)) if (se.fit){ ip<-matrix(ncol=nterms,nrow=NROW(X)) dimnames(ip)<-list(rownames(X),names(asgn)) } avX<-apply(X,2,mean)...

...27377 0.5769836 Here is the relevant section of corrected code: if (type=="terms"){ asgn <- attrassign(object) beta<-coef(object) hasintercept<-attr(tt,"intercept")>0 if (hasintercept) asgn$"(Intercept)"<-NULL nterms<-length(asgn) predictor<-matrix(ncol=nterms,nrow=NROW(X)) dimnames(predictor)<-list(rownames(X),names(asgn)) if (se.fit){ ip<-matrix(ncol=nterms,nrow=NROW(X)) dimnames(ip)<-list(rownames(X),names(asgn)) } if (hasintercept){ # This w...

...utation of the 'ss' terms (line 237 in the file mlm.R in the source code). Changing this (and the following line) by something similar to what is done in summary.manova seems to resolve the problem: comp <- as.matrix(fit$effects)[seq(along=asgn), ,drop=FALSE] uasgn <- unique(asgn) nterms <- length(uasgn) ss <- list(nterms) df <- numeric(nterms) for(i in seq(nterms)) { ai <- (asgn == uasgn[i]) ss[[i]] <- crossprod(comp[ai, ,drop=FALSE]) df[i] <- sum(ai) }

...s the test.cpus() function come from? I couldn't find it in the MASS table of contents on CRAN. Thanks in advance for any help you can give! ######DATASET1, ORIGINAL ORDER > pprfile.ppr <- ppr( + award~ + ilogemp+ilogage, + data=dataset1, nterms=1, max.terms=40, optlevel=3, bass=0 + ) > pprfile.ppr Call: ppr.formula(formula = award ~ ilogemp + ilogage, data = dataset1, nterms = 1, max.terms = 40, optlevel = 3, bass = 0) Goodness of fit: 1 terms 2 terms 3 terms 4 terms 5 terms 6 terms 94153840890 97...

...s (I think it depends on the choose of the parameters) get a error message, but I do not know what it means. After that I tried the procedure with an example dataset R is providing. Although using the cancer dataset I also get this message. Input: survreg(Surv(time, status) ~ pspline(age,degree=0,nterm=4), cancer) Output: Fehler in if (!doing.well && old$half < 2) { : Fehlender Wert, wo TRUE/FALSE n?tig ist I hope you can help me, Thanks Birgit Rauchenschwandtner -- "Feel free" - 10 GB Mailbox, 100 FreeSMS/Monat ...

...hen I decided that I might want additional explanatory variables (other than ilogemp) in my model. The ppr function in modreg seemed a logical extension of supsmu from univariate to multidimensional explanatory variables. As a "check" I ran the following: pprest <- ppr(ilogemp,award,nterms=1), figuring I'd get the same results. I did not. First, the fitted values ppr output is not rescaled back to the original scale of award. Eventually, I figured out that the ppr fitted values had mean zero and variance=1, so I thought I needed to multiply ppr's fitted values by the stan...

...<- function(x) myfile <- lm(award ~ ilogemp + ilogage, x) test.by <- by(wintemp, as.factor(wintemp$group), my.newfun) 2. This does not work (leaving aside whether I am using ppr correctly or not!): > my.pprfun <- function(x) mypprfile <- ppr(award ~ ilogemp + ilogage, data = x, nterms = 5, + max.terms = 10, optlevel = 3) > test.by <- by(wintemp, as.factor(wintemp$group), my.pprfun) Error in model.frame.default(formula = award ~ ilogemp + ilogage, data = x) : Object "x" not found 3. However, this does seem to work, but I don't know enou...

Hi, I am a new user of R using R 2.8.1 in windows 2003. I have a csv file with single column which contain the 30,000 students names. There were typo errors while entering this student names. The actual list of names is < 1000. However we dont have that list for keyword search. I am interested in grouping/cluster these names as those which are similar letter to letter. Are there any

Dear R users, I am looking for the source code of the implementation of ppr (Projection Pursuit Regression) in R. It will be great if citations of the source papers on which the implementation is based, are also provided. Thank you, Arvind Iyer, Grad student, Deptt. of Biomedical Engineering Viterbi School of Engineering University of Southern California, Los Angeles [[alternative HTML

.... By the way, right before Rgui shuts down, the pop-up window suggests it's a runtime error in C++. Here are the codes that cause the crash, library(mlbench) data(BostonHousing2) BH = BostonHousing2[,-c(1:5)] dat1 = BH[1:200,] dat2 = BH[201:400,] mod = ppr(log(cmedv)~., data=dat1, optlevel=0, nterms=2, max.terms=5) pred = predict(mod, newdata=dat2) Thks. HT > sessionInfo() R version 2.11.1 (2010-05-31) i386-pc-mingw32 locale: [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 [3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C [5] LC_TIME=English_United...

...e estimates for each level of the variable "group." After consulting many sources I am stumped as to why the following does not work: > wintemp <- subset(alltemp, winner==1) > my.ppr <- function(x) + { + if(nrow(x) >= 50) { + pprfile <- ppr(award~ilogemp, data=x,nterms=5,max.terms=10,optlevel=3) + summary(pprfile) + } + } > test.by <- by(wintemp,as.factor(wintemp$group),my.ppr) Error in model.frame.default(formula = award ~ ilogemp, data = x) : Object "x" not found Any help would be greatly appreciated. (I am sure I am misunders...

...1749",61187,5705,"sexta-feira ",58 "1762",62973,4829,"sexta-feira ",58 2. Running the next code: data <- read.table('errorexample.txt', header=TRUE,sep=",",dec=".") learner <- 'ppr' learner.pars <- list(Duracao ~ ., nterms=1, data=data, kernel='supsmu', na.action=na.omit, max.terms=5, optlevel=1, sm.method='supsmu', bass=0, span=0) model <- do.call(learner, learner.pars) It works fine. 3. But running: data <- read.table('errorexample.txt', header=TRUE,sep=",",dec=".&...

...ng token error (: ) Stack now 0 1 Shifting token error (: ) Entering state 3 Reading a token: --(end of buffer or a NUL) --EOF (start condition 0) Now at end of input. Cleanup: discarding lookahead token "end of file" (: ) Stack now 0 1 3 Cleanup: popping token error (: ) Cleanup: popping nterm input (: ) <cmdline>:1:34-37: Error: syntax error, unexpected snat add rule ip test input ct status snat ## With dnat Error: popping token "add" (: ) Stack now 0 1 Shifting token error (: ) Entering state 3 Next token is token "dnat" (: ) Error: discarding token "dn...

...11+ X.Iprimnaic.12+X.Iprimnaic.13+X.Iprimnaic.14+X.Iprimnaic.15+X.Iprimnaic.16+ X.Iprimnaic.17+X.Iprimnaic.18+X.Iprimnaic.19+X.Iprimnaic.20+X.Iprimnaic.21+ X.Iprimnaic.22+X.Iprimnaic.23+X.Iprimnaic.24+X.Iprimnaic.25+X.Iprimnaic.26, data=x, nterms=1, max.terms= min(nrow(x),40), optlevel=3 ) #pick number of terms giving best fit numterm <- which.min(pprfile.ppr$gofn[pprfile.ppr$gofn>0]) pprfile.ppr <- ppr( award~ ilogemp+ilogage+sdb+allsmall+ size...

...it returns an error condition I cannot understand. This is what i did/got: > library(modreg) > X <- matrix(scan("miX_e.txt", 0), ncol=2, byrow=TRUE) Read 450 items > Y <- matrix(scan("g1_sr_e.txt", 0), ncol=1, byrow=TRUE) Read 225 items > g1.ppr <-ppr(X,Y, nterms=3, max.terms=5) Error in matrix(smod[q + 6 + p * ml + 1:(q * mu)], q, mu, dimnames = list(ynames, : length of dimnames[1] not equal to array extent Where "miX_e.txt" is a file containing 225 rows (225 cases for training) with 2 columns (2 explanatory variables), and "g1_s...

...@ union yyalloc #endif /* YYFINAL -- State number of the termination state. */ -#define YYFINAL 2 +#define YYFINAL 3 /* YYLAST -- Last index in YYTABLE. */ -#define YYLAST 23 +#define YYLAST 24 /* YYNTOKENS -- Number of terminals. */ #define YYNTOKENS 12 /* YYNNTS -- Number of nonterminals. */ -#define YYNNTS 9 +#define YYNNTS 11 /* YYNRULES -- Number of rules. */ -#define YYNRULES 19 +#define YYNRULES 22 /* YYNRULES -- Number of states. */ -#define YYNSTATES 28 +#define YYNSTATES 30 /* YYTRANSLATE(YYLEX) -- Bison symbol number corresponding to YYLEX. */ #define...

Dear List, How do I extract the approximate Wald test for the frailty (in the following example 17.89 value)? What about the P-values, other Chisq, DF, se(coef) and se2? How can they be extracted? ######################################################> kfitm1 Call: coxph(formula = Surv(time, status) ~ age + sex + disease + frailty(id, dist = "gauss"), data = kidney)

...;-manylm(mvform) > anova(lm,nBoot=500) > plot(lm) However, because these are count data, I am interested in fitting a generalized linear model instead, but then I get following error: > glm<-manyglm(mvform,family="negative.binomial") > anova(glm,nBoot=500) Error in XvarIn[nterms - i, varseq > i] <- 0 : (subscript) logical subscript too long Also, when trying to create diagnostics plots, I get the following error. > plot(glm) Error in plot.window(...) : need finite 'xlim' values In addition: Warning messages: 1: In default.plot.manyglm(x, which = which...