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Time series are data observed over time (either in continuous time or at discrete time periods).

2 votes
2 answers
875 views

Best imputation method for stochastic noisy data?

What is the best imputation method for a dataset consisting of stochastic data? For example, let's say you have a table of security returns. In some cases the missings are random, in other cases are n …
Ram Ahluwalia's user avatar
5 votes
0 answers
865 views

Is there a package in R that calculates the Durbin-Watson test assuming a weighted regression? [closed]

There are several packages that can apply the Durbin-Watson test for serial correlation. However, I do not see a package that supports the calculation in the case that once has a GLS weighted regressi …
Ram Ahluwalia's user avatar
6 votes
2 answers
3k views

Multiple regression with constraints on coefficients [closed]

I am performing a returns analysis. The idea is to regress a time-series of returns on the returns of various asset classes. The beta coefficients must be constrained such that sum of the coefficients …
Ram Ahluwalia's user avatar
5 votes
0 answers
3k views

Random Forests / adaboost in panel regression setting

Tools such as random forests or adaboost are powerful at solving cross-sectional binary logistic problems or prediction problems where there are many weak learners. But can these tools be adapted to s …
Ram Ahluwalia's user avatar
3 votes
2 answers
2k views

Residual analysis of cross-sectional time-series forecasts

I have forecasts and actuals for panel data (i.e. time-series cross-sectional data). The forecasts are already generated and provided by some source outside of R. I'd like to evaluate the quality of t …
Ram Ahluwalia's user avatar