Looks good for me please proceed. Suho
On Tue, Apr 22, 2014 at 6:25 PM, Seshika Fernando <sesh...@wso2.com> wrote: > Hi, > > After researching on how to handle seasonality in regression, I have the > following findings. > > 1. Can use dummy variables to capture seasonality. The user needs to add > dummy variables to the input stream to capture and quantify seasonality in > the regression equation. Therefore, this does not have to be explicitly > implemented since it will be a user input to the generic regression > function. > eg:- If there is a quarterly pattern, user 3 dummy variables to > denote the 4 quarters. (dummy variables are binary variables) > > 2. If seasonality is continuous (i.e. not discrete) for example sinusoidal > or quadratic or exponential, then the regression equation ceases to be > linear and we need to identify the functional form that fits the data set. > Then using that functional form, the user needs to convert it to linear > form, prior to sending the data set to the generic regression function. > eg:- if the dataset is of the form, y ~ Sin(x), then we need to > create a new variable x1 = sin(x) so that we can fit the linear regression > equation y = a + b * x1 > > Once again, we don't have to implement anything in the regression > function, since this adjustment needs to take place before the data set is > sent to the regression function. > > 3. This brings us to the next point and the golden question: how does a > user identify which functional form the dataset fits? Usually, we need to > employ some sort of algorithm to fit a non-linear regression equation like > Gauss-Newton or a graphing mechanism, which unfortunately is out of the > scope of the CEP. > > *Next Steps* > > So considering the above findinds, here are the next steps. > > 1. Create Samples for the following > a) Plain old linear regression (simple and multivariate) > b) Linear regression with dummy variables > c) Linear regression on non-linear dataset, using siddhi queries to > transform functional form to linear prior to sending data to regression > function. > > 2. Document the above samples and complete function documentation > > 3. If and when we come across datasets that follow certain non-linear > functional forms, create simple math functions in siddhi to convert data. > eg:- Sin(x), power(x,n) etc; > > Thats the update as of now. Any thoughts? suggestions? > > > Regards, > Seshika > -- *S. Suhothayan* Associate Technical Lead, *WSO2 Inc. *http://wso2.com * <http://wso2.com/>* lean . enterprise . middleware *cell: (+94) 779 756 757 | blog: http://suhothayan.blogspot.com/ <http://suhothayan.blogspot.com/>twitter: http://twitter.com/suhothayan <http://twitter.com/suhothayan> | linked-in: http://lk.linkedin.com/in/suhothayan <http://lk.linkedin.com/in/suhothayan>*
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