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-1
votes
1answer
215 views

Polynomial in linear regression

I am new to Regression and R. I know that polynomial functions are used when a regression model does not fit data (underfitting), but I want to know which degree of polynomial should be used? I also ...
3
votes
0answers
271 views

Recovering raw coefficients and variances from orthogonal polynomial regression

It seems that if I have a regression model such as $y_i \sim \beta_0 + \beta_1 x_i+\beta_2 x_i^2 +\beta_3 x_i^3$ I can either fit a raw polynomial and get unreliable results or fit an orthogonal ...
2
votes
0answers
40 views

Can the OLS residual variance suggest a polynomial relationship?

I am trying to figure out whether from the following graph of the OLS residuals that the linear relationship does not hold, and that probably a cubic relationship would do better? Since both in the ...
2
votes
0answers
67 views

Orthogonality of Hermite Polynomials

As we know probabilistic Hermite polynomials are orthogonal with respect to the weight function $\frac{1}{\sqrt{2 \pi}} e^{-x^2/2}$ (density of standard normal). I have a distribution which is a ...
1
vote
0answers
40 views

Unit root test for ARIMA models

I have a slight confusion regarding seasonal models and which polynomial to use for conducting unit root tests. Given a model: $\phi(B)\Phi(B^s)\Delta^d\Delta^D_S X_t = \theta(B)\Theta(B^s)\epsilon ...
1
vote
0answers
26 views

nearest neighbors degrees of freedom

For polynomial fitting with a polynomial of degree $n$, we have $n$ degrees of freedom. Is there a similar concept for $k$ nearest neighbors? Is there any way to compare the degrees in general? I come ...
1
vote
0answers
100 views

Determining polynomial model coefficients forcing slope = 1 and intercept =0

I have two observational variables, Cobs and R, both subject to measurement error. I believe that a model of the form Cmod = a0 + a1*R + a2*R^2 + a3*R^3 would be a reasonable representation of the ...
0
votes
0answers
40 views

lm to lmer function tweaking

I have stolen and modified a snippet of code found off the internet from (http://www.r-bloggers.com/aic-bic-vs-crossvalidation/) which graphically depicts AIC and BIC values for different polynomial ...
0
votes
0answers
15 views

orthogonal contrast with an ordinal variable in gam

I am fitting a set of continuous and factor variables into a GAM. The factors are ordinal: they are levels of abundance of specific macroinvertebrates set as "none" (0% cover), "low" (>0-10% cover) ...
0
votes
0answers
98 views

SVM with svm and svmpath function

I am trying to compare the R functions svm (library: e1071) and svmpath (library svmpath). ...
0
votes
0answers
101 views

Model reduction - Backward elimination

The rule I use for reducing covariates (trimming) is as following: Look at the highest order interaction. If that is not significant, drop it. If it is significant, stop. If drop the highest order ...