Dear R-users, This is partially a R question and partially general econometrics.
I have three time series which are somewhat "dissimilar": plotting their histograms indicates that they do not come from the same distribution, never mind a normal distribution. I wish to predict the first as a function of the latter two. I need a regression method which deals with three problems: - I have time series data, so there is likely to be serial correlation between parameters (as a matter of fact, a visual look at the partial autocorrelation of the residuals on a simple linear regression confirms this) - the variables do not come from the same distribution, i.e. their histograms do not look the same and they do not look "normal" - I do not know what those distributions are Is there a method implemented in R which: - can deal with serially correlated data - can deal with data that does not come from the same distribution - can deal with not being told what those distributions are, i.e. can automagically decide a transformation of those variables - provides summary data, such as the residuals, various tests of relevant significance hypothesis, etc. In glm, it appears that you do need to know what the distributions are, so I believe that will not work, but I could be wrong. Any pointers appreciated. Many thanks in advance, Tolga Generally, this communication is for informational purposes only and it is not intended as an offer or solicitation for the purchase or sale of any financial instrument or as an official confirmation of any transaction. In the event you are receiving the offering materials attached below related to your interest in hedge funds or private equity, this communication may be intended as an offer or solicitation for the purchase or sale of such fund(s). All market prices, data and other information are not warranted as to completeness or accuracy and are subject to change without notice. Any comments or statements made herein do not necessarily reflect those of JPMorgan Chase & Co., its subsidiaries and affiliates. This transmission may contain information that is privileged, confidential, legally privileged, and/or exempt from disclosure under applicable law. If you are not the intended recipient, you are hereby notified that any disclosure, copying, distribution, or use of the information contained herein (including any reliance thereon) is STRICTLY PROHIBITED. Although this transmission and any attachments are believed to be free of any virus or other defect that might affect any computer system into which it is received and opened, it is the responsibility of the recipient to ensure that it is virus free and no responsibility is accepted by JPMorgan Chase & Co., its subsidiaries and affiliates, as applicable, for any loss or damage arising in any way from its use. If you received this transmission in error, please immediately contact the sender and destroy the material in its entirety, whether in electronic or hard copy format. Thank you. Please refer to http://www.jpmorgan.com/pages/disclosures for disclosures relating to UK legal entities. [[alternative HTML version deleted]] ______________________________________________ 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.
