search for: ur2

...found and what could be a solution. I´m working with R 2.4.0 on windows XP, and here is a reproducible example, (this example is just to show the problems in the plot and it doesn't make any sense the way I analyzed). set.seed(3) datos <-data.frame(fac.A=rep(c("bla","Ur2","pel","arb"),each=3), y= c(rnorm(3,sd=0.5),rnorm(9,sd=2))) model1 <- lm(y~fac.A,data=datos) plot(model1,which=5) # plot1 # this plot1 show that level "arb" has less dispersion than the other levels, # But if I do the plot by...

Hi people, I want to obtain the adjusted r-square given a set of coefficients (without the intercept), and I don't know if there is a function that does it. Exist???????????????? I know that if you make a linear regression, you enter the dataset and have in "summary" the adjusted r-square. But this is calculated using the coefficients that R obtained,and I want other coefficients

...iroot(function(q) pnbinom(q, mu=3, size=1e-4) - 0.9999, c(7000,8000))) ## List of 5 ## $ root : num 7942 ## $ f.root : num 1.52e-09 ## $ iter : int 18 ## $ init.it : int NA ## $ estim.prec: num 6.49e-05 ## and this of course does not change when asking for more precision : str(ur2 <- uniroot(function(q) pnbinom(q, mu=3, size=1e-4) - 0.9999, c(7000,8000), tol=1e-12)) ## List of 5 ## $ root : num 7942 <<< correct is 7942, not 8044 !!! ## $ f.root : num 1.52e-09 ## $ iter : int 47 ## $ init.it : int NA ## $ estim.prec: num 7.28e-12 ----------...

Thanks Ben for verifying the issue. It is always reassuring to hear when others can reproduce the problem. I wrote a small patch that fixes the issue (https://github.com/r-devel/r-svn/pull/11): diff --git a/src/nmath/qnbinom.c b/src/nmath/qnbinom.c index b313ce56b2..d2e8d98759 100644 --- a/src/nmath/qnbinom.c +++ b/src/nmath/qnbinom.c @@ -104,6 +104,7 @@ double qnbinom(double p, double size,

...iroot(function(q) pnbinom(q, mu=3, size=1e-4) - 0.9999, c(7000,8000))) ## List of 5 ## $ root : num 7942 ## $ f.root : num 1.52e-09 ## $ iter : int 18 ## $ init.it : int NA ## $ estim.prec: num 6.49e-05 ## and this of course does not change when asking for more precision : str(ur2 <- uniroot(function(q) pnbinom(q, mu=3, size=1e-4) - 0.9999, c(7000,8000), tol=1e-12)) ## List of 5 ## $ root : num 7942 <<< correct is 7942, not 8044 !!! ## $ f.root : num 1.52e-09 ## $ iter : int 47 ## $ init.it : int NA ## $ estim.prec: num 7.28e-12 ----------...

...k{u<M_OE`poMp<~3{pNXZA%ZQgStz2ocsSgSP>B at Tk z-goa(#L{4^7_h$RQ{-6{$c(to!OzJlwOC?iHi^W=@)WigdKGG`sZmv8O{Ld~Gz%Y! z$}l7k<M3|j(6 at +xO3W#<rvDu-Kk~8Nd)ai(q!a%(#gUo}4HC_mHo361=`AA7N|ZVV zJxk;*QIS)IF}GP>JvF!XDJ^=gB6jDAt2C=6>l;H?Np7P5&eN=u0`e_;j{|+7VED+L zGOQB}&)H4of#rm0ZyCqjUR2}?BnnmMI9mV93*6=+c>r9M7BT(J8H>_Wy)rB70;_KI z(OP17%ddlQI~mWu!=fE7Kx^a`=$bLJJ>3-|P|xf;Ff!Ume+#OPP<~_IAAB`5zZXHc z8q_O8TEh2|_?trWzsP6|Uw-xx+q^M&WP2=SOyf~=j$0|H{3i}Tc at HL=*oL$aTQ0d( zJWsj8{-H>&@;|5dd!0sE#mcG5|5ln;KAv{S)jIQcqI}2pgbstvFH6oB4pf)@d^!$A zRk}*Fe{?2-YV3g!thnqPShNmFmJPn...