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> It depends on what you consider reasonable. > > The processing time of file operation that iterates through a mailbox > will generally go up proportinately with size.? If you do a text search > without some indexing system like Solr, it will take a very long time. > > If the mailbox is just some archive that you pile up and forget about it > except for once in a blue moon retrieval, then it might be reasonable. > > If it's a...

Hi all!! I am using a proportinal odds model to study some ordered categorical data. I am trying to predict one ordered categorical variable taking into account only another categorical variable. I am using polr from the R MASS library. It seems to work ok, but I'm still getting familiar and I don't know how to assess go...

Hi all!! I am using a proportinal odds model to study some ordered categorical data. I am trying to predict one ordered categorical variable taking into account only another categorical variable. I am using polr from the R MASS library. It seems to work ok, but I'm still getting familiar and I don't know how to assess go...

I''m using a fairly large number of classes, andf borrowing is not working as expected... I''ve called this setting it up on an IMQ device with speed 1200/256 on a 1536/384 line. I''m then throwing a UDP data transfer at it that gets tossed in one of the class under parent 1:6. The classification is working fine, but when I try to ping out, ping times are in the 900ms

Greetings, I have several users who have inboxes that are over 20 GB. Lately I have noticed Dovecot logs say it's taking over 30 seconds to sync their mailboxes. As email admins,? how do you handle inboxes that are so large? Do you use mailbox types that have better performance like dbox? We're using maildir. What's a reasonable inbox size?? Is 20+ GB reasonable and nothing to

...have better performance like dbox? We're using maildir. > > What's a reasonable inbox size? Is 20+ GB reasonable and nothing to worry > about? It depends on what you consider reasonable. The processing time of file operation that iterates through a mailbox will generally go up proportinately with size. If you do a text search without some indexing system like Solr, it will take a very long time. If the mailbox is just some archive that you pile up and forget about it except for once in a blue moon retrieval, then it might be reasonable. If it's an active mailbox, it will be...

On Fri, 8 May 2020, asai at globalchangemusic.org wrote: > >> It depends on what you consider reasonable. >> >> The processing time of file operation that iterates through a mailbox >> will generally go up proportinately with size. If you do a text search >> without some indexing system like Solr, it will take a very long time. >> >> If the mailbox is just some archive that you pile up and forget about it >> except for once in a blue moon retrieval, then it might be reasonable. >&g...

Dear Dr. Fieberg, you used a regression tree approach to explore ordinal data set in addition to the proportinal odds model. I find this very interesting. I would like to know, how good the results of the regression tree approach turned out in comparison to the proportional odds model. Since people very often treat ordinal data as continuous, I would like to know how successfull this strategy is. I mean,...

...nd L2 penalties). Glmnet uses pathwise coordinate descent, and is very fast. The current list of models covered are: least squares linear regression binary logistic regression multinomial logistic regression (grouped and ungrouped) poisson regression multi-response linear regression (grouped) Cox proportinal-hazards model Some of the features of glmnet: * By default it computes the path at 100 uniformly spaced (on the log scale) values of the regularization parameter lambda. Alternatively users can provide their own values of lambda * Recognizes and exploits sparse input matrices (ala Matrix pa...

...nd L2 penalties). Glmnet uses pathwise coordinate descent, and is very fast. The current list of models covered are: least squares linear regression binary logistic regression multinomial logistic regression (grouped and ungrouped) poisson regression multi-response linear regression (grouped) Cox proportinal-hazards model Some of the features of glmnet: * By default it computes the path at 100 uniformly spaced (on the log scale) values of the regularization parameter lambda. Alternatively users can provide their own values of lambda * Recognizes and exploits sparse input matrices (ala Matrix pa...

What function and package I use to conduct ordinal regression?? My data is composed 2colums and 180rows. The first colum indicate level of mass and second colum is intensity. So, I want to calculate how much intensity are related mass. [[alternative HTML version deleted]]