[R] execute functions in .dll
Dear all, We have a data base with huge amounts of data that we want analysts/scientists to be able to use. These data can be accessed through the internet thanks to a SOAP based web service that we have set up. We have also developed a web service client using Dot.NET framework, which is built into a .dll file. I now wonder, do you know of a way to execute the functions in .dll files from within R? Thanks, Tord __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] execute functions in .dll
Dear all, We have a data base with huge amounts of data that we want analysts/scientists to be able to use. These data can be accessed through the internet thanks to a SOAP based web service that we have set up. We have also developed a web service client using Dot.NET framework, which is built into a .dll file. I now wonder, do you know of a way to execute the functions in .dll files from within R? Thanks, Tord __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] opposite estimates from zeroinfl() and hurdle()
Dear all, A question related to the following has been asked on R-help before, but I could not find any answer to it. Input will be much appreciated. I got an unexpected sign of the slope parameter associated with a covariate (diam) using zeroinfl(). It led me to compare the estimates given by zeroinfl() and hurdle(): The (significant) negative estimate here is surprising, given the biology of the species: summary(zeroinfl(bnl ~ 1| diam, dist = poisson, data = valdaekar, EM = TRUE)) Count model coefficients (poisson with log link): Estimate Std. Error z value Pr(|z|) (Intercept) 3.74604 0.02635 142.2 2e-16 *** Zero-inflation model coefficients (binomial with logit link): Estimate Std. Error z value Pr(|z|) (Intercept) 21.7510 7.6525 2.842 0.00448 ** diam -1.1437 0.3941 -2.902 0.00371 ** Number of iterations in BFGS optimization: 1 Log-likelihood: -582.8 on 3 Df The hurdle model gives the same estimates, but with opposite (and expected) signs of the parameters: summary(hurdle(bnl ~ 1| diam, dist = poisson, data = valdaekar)) Count model coefficients (truncated poisson with log link): Estimate Std. Error z value Pr(|z|) (Intercept) 3.74604 0.02635 142.2 2e-16 *** Zero hurdle model coefficients (binomial with logit link): Estimate Std. Error z value Pr(|z|) (Intercept) -21.7510 7.6525 -2.842 0.00448 ** diam 1.1437 0.3941 2.902 0.00371 ** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Number of iterations in BFGS optimization: 8 Log-likelihood: -582.8 on 3 Df Why is this so? thanks, Tord Windows NT, R 2.8.1, pcsl 1.03 -- Tord Snäll Department of Ecology / Swedish Species Information Centre Swedish University of Agricultural Sciences (SLU) P.O. 7044, SE-750 07 Uppsala, Sweden Office/Mobile/Fax +46-18-672612/+46-76-7662612/+46-18-673537 www.ekol.slu.se/staff_tordsnall www.artdata.slu.se/personal/fototsn.asp __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] opposite estimates from zeroinfl() and hurdle()
Dear all, A question related to the following has been asked on R-help before, but I could not find any answer to it. Input will be much appreciated. I got an unexpected sign of the slope parameter associated with a covariate (diam) using zeroinfl(). It led me to compare the estimates given by zeroinfl() and hurdle(): The (significant) negative estimate here is surprising, given the biology of the species: summary(zeroinfl(bnl ~ 1| diam, dist = poisson, data = valdaekar, EM = TRUE)) Count model coefficients (poisson with log link): Estimate Std. Error z value Pr(|z|) (Intercept) 3.746040.02635 142.2 2e-16 *** Zero-inflation model coefficients (binomial with logit link): Estimate Std. Error z value Pr(|z|) (Intercept) 21.7510 7.6525 2.842 0.00448 ** diam -1.1437 0.3941 -2.902 0.00371 ** Number of iterations in BFGS optimization: 1 Log-likelihood: -582.8 on 3 Df The hurdle model gives the same estimates, but with opposite (and expected) signs of the parameters: summary(hurdle(bnl ~ 1| diam, dist = poisson, data = valdaekar)) Count model coefficients (truncated poisson with log link): Estimate Std. Error z value Pr(|z|) (Intercept) 3.746040.02635 142.2 2e-16 *** Zero hurdle model coefficients (binomial with logit link): Estimate Std. Error z value Pr(|z|) (Intercept) -21.7510 7.6525 -2.842 0.00448 ** diam 1.1437 0.3941 2.902 0.00371 ** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Number of iterations in BFGS optimization: 8 Log-likelihood: -582.8 on 3 Df Why is this so? thanks, Tord Windows NT, R 2.8.1, pcsl 1.03 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
