Re: [Scilab-users] {EXT} Can you suggest a more efficient procedure for generating random variables?
I am happy to write a 1.5 page technical note. What would we do with it Greetings from Heinz > On 18.03.2019, at 17:27, Claus Futtrup wrote: > > Hi there > > Interesting ... > > If this is excellent for Monte-Carlo simulations, I wish that such an example > is put into the documentation. Lots of people (who need Monte-Carlo) would > then accidentally fall over it and take advantage of it. > > Cheers, > Claus > >> On 18.03.2019 11:06, Heinz Nabielek wrote: >> Ingenious. Works with precision. Gigantically fast for a million random >> deviates. Ideal for Monte-Carlo simulations. >> >> I had never heard of dsearch* before.. >> Thanks a lot >> Heinz >> >> >> * I wished the Scilab help files would be more readable. >> >>> On 18.03.2019, at 09:50, Dang Ngoc Chan, Christophe >>> wrote: >>> >>> Hello Heinz, >>> De : Heinz Nabielek Envoyé : dimanche 17 mars 2019 23:50 I need to generate random deviates x according to a given cumulative distribution y that is available only in tabular form. [...] for i=1:N; x=[x find(y>z(i),1)]; end; y is a previously defined table with values monotonically increasing from zero >>> I guess these are quantiles. >>> >>> I think you can vectorise with something like >>> >>> x = dsearch(z, y) >>> >>> I tried a little bit and it seems to work but I don't know the exact >>> application so... >>> >>> HTH >>> >>> -- >>> Christophe Dang Ngoc Chan >>> Mechanical calculation engineer >>> >>> Public >>> This e-mail may contain confidential and/or privileged information. If you >>> are not the intended recipient (or have received this e-mail in error), >>> please notify the sender immediately and destroy this e-mail. Any >>> unauthorized copying, disclosure or distribution of the material in this >>> e-mail is strictly forbidden. >>> ___ >>> users mailing list >>> users@lists.scilab.org >>> http://lists.scilab.org/mailman/listinfo/users >> ___ >> users mailing list >> users@lists.scilab.org >> http://lists.scilab.org/mailman/listinfo/users > > > > --- > This email has been checked for viruses by Avast antivirus software. > https://www.avast.com/antivirus > > ___ > users mailing list > users@lists.scilab.org > http://lists.scilab.org/mailman/listinfo/users ___ users mailing list users@lists.scilab.org http://lists.scilab.org/mailman/listinfo/users
Re: [Scilab-users] {EXT} Can you suggest a more efficient procedure for generating random variables?
Hi there Interesting ... If this is excellent for Monte-Carlo simulations, I wish that such an example is put into the documentation. Lots of people (who need Monte-Carlo) would then accidentally fall over it and take advantage of it. Cheers, Claus On 18.03.2019 11:06, Heinz Nabielek wrote: Ingenious. Works with precision. Gigantically fast for a million random deviates. Ideal for Monte-Carlo simulations. I had never heard of dsearch* before.. Thanks a lot Heinz * I wished the Scilab help files would be more readable. On 18.03.2019, at 09:50, Dang Ngoc Chan, Christophe wrote: Hello Heinz, De : Heinz Nabielek Envoyé : dimanche 17 mars 2019 23:50 I need to generate random deviates x according to a given cumulative distribution y that is available only in tabular form. [...] for i=1:N; x=[x find(y>z(i),1)]; end; y is a previously defined table with values monotonically increasing from zero I guess these are quantiles. I think you can vectorise with something like x = dsearch(z, y) I tried a little bit and it seems to work but I don't know the exact application so... HTH -- Christophe Dang Ngoc Chan Mechanical calculation engineer Public This e-mail may contain confidential and/or privileged information. If you are not the intended recipient (or have received this e-mail in error), please notify the sender immediately and destroy this e-mail. Any unauthorized copying, disclosure or distribution of the material in this e-mail is strictly forbidden. ___ users mailing list users@lists.scilab.org http://lists.scilab.org/mailman/listinfo/users ___ users mailing list users@lists.scilab.org http://lists.scilab.org/mailman/listinfo/users --- This email has been checked for viruses by Avast antivirus software. https://www.avast.com/antivirus ___ users mailing list users@lists.scilab.org http://lists.scilab.org/mailman/listinfo/users
Re: [Scilab-users] {EXT} Can you suggest a more efficient procedure for generating random variables?
Hello, > De : Heinz Nabielek [mailto:heinznabie...@me.com] > Envoyé : lundi 18 mars 2019 11:07 > > I had never heard of dsearch* before.. Neither did I :-D I just couldn't imagine such a feature didn't exist so I looked at the neighbouring "Search and sort" functions in the help online page… > * I wished the Scilab help files would be more readable... You're probably right. I just wonder how in this case. Maybe adding "dsearch" to the "See also" list at the bottom of the "find" help page? It may deserve a "wishlist" severity on http://bugzilla.scilab.org Anyway, I'm happy I could be useful to someone today (-: -- Christophe Dang Ngoc Chan Mechanical calculation engineer Public This e-mail may contain confidential and/or privileged information. If you are not the intended recipient (or have received this e-mail in error), please notify the sender immediately and destroy this e-mail. Any unauthorized copying, disclosure or distribution of the material in this e-mail is strictly forbidden. ___ users mailing list users@lists.scilab.org http://lists.scilab.org/mailman/listinfo/users
Re: [Scilab-users] {EXT} Can you suggest a more efficient procedure for generating random variables?
Ingenious. Works with precision. Gigantically fast for a million random deviates. Ideal for Monte-Carlo simulations. I had never heard of dsearch* before.. Thanks a lot Heinz * I wished the Scilab help files would be more readable. > On 18.03.2019, at 09:50, Dang Ngoc Chan, Christophe > wrote: > > Hello Heinz, > >> De : Heinz Nabielek >> Envoyé : dimanche 17 mars 2019 23:50 >> >> I need to generate random deviates x according to a given cumulative >> distribution y that is available only in tabular form. >> [...] >> for i=1:N; >> x=[x find(y>z(i),1)]; >> end; >> >> y is a previously defined table with values monotonically increasing from >> zero > > I guess these are quantiles. > > I think you can vectorise with something like > > x = dsearch(z, y) > > I tried a little bit and it seems to work but I don't know the exact > application so... > > HTH > > -- > Christophe Dang Ngoc Chan > Mechanical calculation engineer > > Public > This e-mail may contain confidential and/or privileged information. If you > are not the intended recipient (or have received this e-mail in error), > please notify the sender immediately and destroy this e-mail. Any > unauthorized copying, disclosure or distribution of the material in this > e-mail is strictly forbidden. > ___ > users mailing list > users@lists.scilab.org > http://lists.scilab.org/mailman/listinfo/users ___ users mailing list users@lists.scilab.org http://lists.scilab.org/mailman/listinfo/users
Re: [Scilab-users] {EXT} Can you suggest a more efficient procedure for generating random variables?
Hello Heinz, > De : Heinz Nabielek > Envoyé : dimanche 17 mars 2019 23:50 > > I need to generate random deviates x according to a given cumulative > distribution y that is available only in tabular form. > [...] > for i=1:N; > x=[x find(y>z(i),1)]; > end; > > y is a previously defined table with values monotonically increasing from zero I guess these are quantiles. I think you can vectorise with something like x = dsearch(z, y) I tried a little bit and it seems to work but I don't know the exact application so... HTH -- Christophe Dang Ngoc Chan Mechanical calculation engineer Public This e-mail may contain confidential and/or privileged information. If you are not the intended recipient (or have received this e-mail in error), please notify the sender immediately and destroy this e-mail. Any unauthorized copying, disclosure or distribution of the material in this e-mail is strictly forbidden. ___ users mailing list users@lists.scilab.org http://lists.scilab.org/mailman/listinfo/users
