All Questions
5
questions
2
votes
1
answer
39
views
Why might the functional form of a distribution be "inappropriate" for a particular application?
Working through Bishop's Pattern Recognition and Machine Learning(a great read so far!) and on page 67 he says:
"One limitation of the parametric approach is that it assumes a specific ...
- 1,617
0
votes
0
answers
337
views
Is a non-parametric density estimation required for a bimodal distribution?
How to approach the following two cases is clear, I am mentioning them to set up my question.
(Case 1): For data that appears to be a Gaussian distribution, we can assume the distribution is Gaussian ...
- 893
2
votes
1
answer
839
views
Convergence of kernel density estimate as the sample size grows
Let $X\sim\text{Normal}(0,1)$ and let $f_X$ be its probability density function. I conducted some numerical experiments in the software Mathematica to estimate $f_X$ via a kernel method. Let $\hat{f}...
- 285
1
vote
1
answer
160
views
Credibility evaluation - how to model conditional continuous density from multiple variables of various types?
I recently got dataset for 37000 households with declared income and a few dozens of other variables of various types: continuous, discrete, binary.
The task is to automatically (unsupervised) ...
- 421
3
votes
3
answers
223
views
Literature on nonparametric density estimation
I am about to write my bachelor thesis about non-parametric density estimation, especially kernel density estimators and their application in classification. As I am quite new to looking for academic ...
- 33