All Questions
Tagged with nonparametric regression
170
questions
1
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0
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141
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how well would a robust mixed model fit these data? R (rlmer)
I want to investigate Y ~ X1 * X2 + (1|ID on this dataset (there's a plot of these data in that post too, it's the same dataframe)
Y is a continuos outcome ...
- 781
2
votes
1
answer
145
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MARS vs. CART regression predictive power
I have been wondering recently about the prediction power of the two similar models: Decision Trees and the MARS model (instead of fitting the mean to the subsets, OLS line is estimated). Given that ...
- 205
1
vote
1
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86
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Does the P value need to be "back- transformed" after logging one variable in Regression analyse?
I have a data series, sediment concentration in water Vs Time. The data is not normal but I want to use regression and so have logged the sediment concentration (log10(x)). The residual and fit to ...
- 11
2
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26
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Sample size planning method differs from analysis method
I have seen some articles using one method for sample size estimation(two sample comparison for means or proportions) and subsequently using regression analysis/non parametric methods.
If I have a ...
- 1,445
6
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4
answers
3k
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Is there a non-parametric form of a 3-way ANOVA?
I am currently in the process of writing a publication about the home range of cat shark species in South Africa. However, I am currently struggling with how to create an interaction model of shark ...
- 61
1
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0
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23
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Design points of local polynomial regression
Let the random set $\{(Y_{t},X_t)\}_{t=1}^n$ follow the model:
$$Y_t=m(X_t)+\epsilon_t,\quad t\in\{1,\cdots,n\}\quad (1)$$
where $\epsilon_t$ is a random error term and $m(\cdot)$ is an unknown smooth ...
- 1,097
4
votes
2
answers
1k
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How to create a B-spline basis without intercept and linear trend included?
I want to fit the following model using splines:
\begin{align} Y(t) = \beta_0 + \beta_1t + \sum_{j=2}^{d} \beta_jB(t)_j \end{align}
where $B_j$ are the basis functions. However, when I run the ...
2
votes
1
answer
737
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Is Kernel-Regression parametric or non-parametric?
As the title says, is kernel regression a parametric or non-parametric method, and how can this be motivated/explained?
- 35
0
votes
1
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575
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Closed form equations for simple linear regression estimators
I'm learning specifically about different forms of simple linear regression including ordinary least squares, median absolute deviation, and Theil-Sen. I have no background whatsoever in linear ...
- 89
0
votes
2
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170
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can daily count data use GAM ordered categorical family, proportional-odds model?
The observed response variable Y takes on one of K(=21) ordered categories.
Here is a summary of my response data (count data: the number of hospital admission in each day), y has observations across ...
- 37
5
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131
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How can I make a prediction interval for a future response (not its mean) in regression by using bootstrap?
I'd like to know how I can use bootstrap to predict the confidence interval for a future response (not for its mean) no matter what theorical model and error distribution are, I know I can train the ...
- 1,220
1
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1
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477
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Difference between kernel linear regression and non-parametric regression
A quick perplexity popped up in my mind while reading about non-parametric linear regression.
In linear regression, we model our response $\textbf{y} \sim \mathcal{N}(X\beta, \sigma^2I)$ so basically ...
- 637
1
vote
1
answer
365
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What would be the interpretation of asymmetric kernels in Gaussian Process Regression?
This paper involves with asymmetric Kernels. They claim that this arises due to local parameters. But this is not really true. They induce a particular asymmetric structure in the Kernel yet still ...
- 312
0
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0
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607
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No significant interaction in OLS, but significant in pairwise comparison
I have two independent categorical variables — (i) A: {1, 2, 3}, (ii) B: {0, 1} — with a continuous outcome variable ...
0
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1
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57
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Validity of multilevel modeling to include results for multiple psychometric tests with subscales #statsnube
I have survey data for approx n = 1650 for multiple psychometric tests (all participants have completed all the tests), and about 12 outcome variables (from a PCA of a 52-question survey, e.g. ...
- 11