search for: teststatistic

...(2,3,4), x1=c(1,2), x2=c(1,2)) library(mboost) bd=boost_dpp(y ~ .,data=dt, weights = NULL) blackboost_fit(bd, tree_controls = ctree_control( teststat = "max", testtype = "Teststatistic", mincriterion = 0, maxdepth = 2 ), fitmem = ctree_memory( bd, TRU...

...* log(10*p/1*(1 - p)) } CSAdaExp <- Family(ngradient = ngradient, loss = loss, offset = offset); model.blackboost <- blackboost(tr[,1:DIM], tr.y, family=CSAdaExp, weights=tr.w, control=boost_control(mstop=100, nu=0.1), tree_controls=ctree_control(teststat = "max",testtype = "Teststatistic",mincriterion = 0,maxdepth = 10)); or #loss <- function (y, f) #{ # exp(-y * f * ifelse(y==1,COST_FN,COST_FP)) #} #ngradient <- function (y, f, w = 1) #{ # y * ifelse(y==1,COST_FN,COST_FP) * exp(-y * f * ifelse(y==1,COST_FN,COST_FP)) #} #offset <- function (y, w) #{ # p &lt...

...'m having problems to determine the cointegration rank of my data set using the Johnasen's trace test. This trace test is already programmed in the package ur.ca and can be found in the function ca.jo(). After I run the ca.jo() function on my data set I get the following output: Values of teststatistic and critical values of test: test 10pct 5pct 1pct r<=10 9.71 7.52 9.24 12.97 r<=9 24.18 17.85 19.96 24.6 r<=8 45.16 32 34.91 41.07 r<=7 74.12 49.65 53.12 60.16 r<=6 113.96 71.86 76.07 84.45 r<=5 158.58 97.18 102.14 111.01 r<=4 207.95 126.58 131.7 143.09 r<=3 278.29 159.48...

Dear R-users I need to calibrate kappa, rho, eta, theta, v0 in the following code, see below. However when I run it, I get: y <- function(kappahat, rhohat, etahat, thetahat, v0hat) {sum(difference(k, t, S0, X, r, implvol, q, kappahat, rhohat, etahat, thetahat, v0hat)^2)} > nlminb(start=list(kappa, rho, eta, theta, v0), objective = y, lower =lb, > upper =ub) Error in dots[[1L]][[1L]] :

Hi, Could anyone help me understand how the mincriterion threshold works in ctree and cforest of the party package? I've seen examples which state that to satisfy the p < 0.05 condition before splitting I should use mincriterion = 0.95 while the documentation suggests I should use mincriterion = qnorm(0.95) which would obviously feed the function a different value. Thanks in advance,

Fedora 9 R 2.7.1 I tried to install R on my Linux system using install.packages("Rcmdr", dependencies=TRUE). I received many, many, many error messages. I hope someone can suggest a fix. The output from warnings() is listed below. A more detailed list of errors from one of the failed installations is listed below the warnings: > warnings() Warning messages: 1: In