Financial professional with expertise in financial modeling, risk management, and related quantitative methods including Monte Carlo simulation, linear and logit regression, and statistical hypotheses testing. For past few years have been engaged in developing econometrics models related to Stress testing for a large financial institution.

Feb
24
awarded Benefactor
Feb
23
comment Mann-Whitney test
Hannah, as a matter of consistency, given that you have given me "best answer" can you also give me one helpful vote. Thanks.
Feb
23
comment AR terms and independent variable as regressors
kashili khashili, given that you have given me best answer, as a matter of consistency can you also give me a helpful vote. Thanks.
Feb
23
comment When to create a control group with paired T test
z x, just as a minor detail, someone who has given the best answer, by definition also has given a useful answer. As a matter of consistency, can you give me a "useful vote."
Feb
23
accepted How to interpret the direction of the Harvey-Collier test and Rainbow test for linearity?
Feb
21
comment How to interpret the direction of the Harvey-Collier test and Rainbow test for linearity?
Ben, this is very helpful. What I get from Rs info is that the Harvey-Collier test tests the nonlinearity of the residuals. Meanwhile, the Rainbow test tests the nonlinearity of the actual model. Actually, ultimately both mean somewhat the same thing (nonlinear relationship with a linear model will have nonlinear residuals). Is that how you see it?
Feb
16
awarded Promoter
Feb
14
awarded Popular Question
Feb
13
asked How to interpret the direction of the Harvey-Collier test and Rainbow test for linearity?
Jan
20
comment When to create a control group with paired T test
It is not the same thing. The paired t test tells you how patients fared after taking the drug. The unpaired one tells you if the drug is more effective than a placebo. The unpaired t test is statistically and clinically a more rigorous test. The paired t test result could simply be due to the passage of time (with time patients just got better). The unpaired t test, as structured, controls for that with a Control Group.
Jan
20
answered When to create a control group with paired T test
Jan
15
comment How to detect noisy entries in the data set
Well, that's what Anony-Mousse suggests. I am not familiar with that technique. The first question I would raise is will it work with your logistic regression framework?
Jan
13
comment How to detect noisy entries in the data set
Without knowing how you want to use the data, you can't answer this question. If we knew that you wanted to develop a model to estimate X1 by using X2-X7 as independent variables; once you had developed such a model we could look for outliers among the residuals using various metrics (D's Cook, leverage-Halt, studentized residuals). And, using such metrics we could identify datapoints with too much influence on the coefficients. And, rerun the model without such outliers. But, I don't know what you want to achieve with this data. You can't identify the noise before specifying the model.
Jan
12
awarded Nice Question
Jan
9
comment How do I read this linear model output from R?
Your design structure seems completely different from your model one. The design appears to cater to a paired hypothesis testing framework (difference between same group before and after treatment). Appropriate tests would be paired student t test or its nonparametric equivalents. In this framework, you would not even need a Control group (and I don't know why you need one). But, your R codes clearly suggests this is a multiple regression models with the variables as specified. It seems you should respecify your statistical model completely differently, as suggested.
Jan
9
answered How do I read this linear model output from R?
Dec
14
accepted What are the three forms of the Park test for heteroskedasticity?
Dec
13
answered Why is homogeneity of variance so important?
Dec
12
revised How to use the Glejser test?
added 301 characters in body
Dec
12
comment What are the three forms of the Park test for heteroskedasticity?
gung, I am aware that the Park test has some problems. However, those may not necessarily have anything to do with the independent variables being correlated or even more so... multi collinear. Thanks much for digging out who the professor is who mentioned the three forms of the Park test. I will contact him.
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