search for: 4e5

...K). cc -ieee_with_inexact -g -I../include -I../../src/include -c pnf.c -o pnf.o cc -ieee_with_inexact -g -I../include -I../../src/include -c pnt.c -o pnt.o cc: Error: pnt.c, line 83: In this statement, "1021" is not an lvalue, but occurs in a context that requires one. if (df > 4e5 || del*del > 2*M_LN2*(-DBL_MIN_EXP)) { ---------------------------------------^ gmake[2]: *** [pnt.o] Error 1 gmake[2]: Leaving directory `/home/ming/R-0.64.0/src/nmath' gmake[1]: *** [R] Error 1 gmake[1]: Leaving directory `/home/ming/R-0.64.0/src' gmake: *** [R] Error 1 When I change...

...her... change -PIC with -KPIC enjoy, tim... === diff -ru orig/R-0.64.0/src/nmath/pnt.c R-0.64.0/src/nmath/pnt.c --- orig/R-0.64.0/src/nmath/pnt.c Wed Apr 7 02:45:48 1999 +++ R-0.64.0/src/nmath/pnt.c Sat Apr 10 13:02:45 1999 @@ -80,7 +80,7 @@ del = -del; } - if (df > 4e5 || del*del > 2*M_LN2*(-DBL_MIN_EXP)) { + if (df > 4e5 || del*del > 2*M_LN2*(-(DBL_MIN_EXP))) { /*-- 2nd part: if del > 37.62, then p=0 below FIXME: test should depend on `df', `tt' AND `del' ! */ /* Approx. from Abramowitz & Stegun 26.7.10 (...

...c calculates the value as val =? (n > x * x) ? pbeta (x * x / (n + x * x), 0.5, n / 2, /*lower_tail*/0, log_p) : pbeta (n / (n + x * x), n / 2.0, 0.5, /*lower_tail*/1, log_p); thus avoiding the loss of accuracy in the pbeta routine when 1-1./nx is calculated. It also makes the if (n > 4e5) { /*-- Fixme(?): test should depend on `n' AND `x' ! */ ??? /* Approx. from? Abramowitz & Stegun 26.7.8 (p.949) */ ??? val = 1./(4.*n); ??? return pnorm(x*(1. - val)/sqrt(1. + x*x*2.*val), 0.0, 1.0, ???????? lower_tail, log_p); } code unneccessary. Ian Smith Personally, I think t...

Hi, I am trying to fi a glm-poisson model to 400.000 records. I have tried biglm and glmulti but i have problems... can it really be the case that 400.000 are too many records??? I am thinking of using random samples of my dataset..... Many thanks, -- View this message in context: http://r.789695.n4.nabble.com/glm-poisson-fitting-400-000-records-tp3925100p3925100.html Sent from the R help

...----------------------- Here is the patch --------------------------------------------------------------------- --- src/nmath/pt.c.~1~ Wed Feb 3 12:21:46 1999 +++ src/nmath/pt.c Wed Mar 10 18:15:42 1999 @@ -41,6 +41,11 @@ if(!finite(n)) return pnorm(x, 0.0, 1.0); #endif + if (n > 4e5) { /*-- Fixme(?): test should depend on `n' AND `x' ! */ + /* Approx. from Abramowitz & Stegun 26.7.8 (p.949) */ + val = 1./(4.*n); + return pnorm(x*(1. - val)/sqrt(1. + x*x*2.*val), 0.0, 1.0); + } val = 0.5 * pbeta(n / (n + x * x), n / 2.0, 0.5); return (x > 0.0) ? 1 -...

I have come across the following situation when using the function pt which calls the student t distribution function. I simulate data from a normal distribution and fit the student t. The estimated degrees of freedom gets larger at each iteration and there is no convergence. It seems there should be some mechanism where it switched to a normal distribution when the degrees of freedom gets

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