Last updated: 2018-05-30

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✔ Repository version: 38e8063
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Ignored files:
    Ignored:    .Rhistory
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    Ignored:    log/

Untracked files:
    Untracked:  analysis/binom.Rmd
    Untracked:  analysis/glm.Rmd
    Untracked:  analysis/overdis.Rmd
    Untracked:  analysis/smashtutorial.Rmd
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    Modified:   analysis/ashpmean.Rmd
    Modified:   analysis/nugget.Rmd
```
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File	Version	Author	Date	Message
Rmd	38e8063	Dongyue	2018-05-30	covariate iterative
html	4b0e6c4	Dongyue	2018-05-25	edit
Rmd	d810c3e	Dongyue	2018-05-25	edit
html	568cf1a	Dongyue	2018-05-24	edit
Rmd	35cc4d6	Dongyue	2018-05-24	edit
Rmd	ec87323	Dongyue	2018-05-24	edit
html	511adb2	Dongyue	2018-05-19	wave basis
Rmd	0f77e70	Dongyue	2018-05-19	wave basis
html	4b2e5d1	Dongyue	2018-05-17	add known version
Rmd	bdddcf6	Dongyue	2018-05-14	edit
Rmd	7ee9791	Dongyue	2018-05-14	edit
html	5f9b5c6	Dongyue	2018-05-09	edit
Rmd	fda2411	Dongyue	2018-05-09	one iteration ash poisson
html	3a42238	Dongyue	2018-05-08	correction
Rmd	910bc07	Dongyue	2018-05-08	correction
html	cb91cb1	Dongyue	2018-05-08	add robust
Rmd	2e73919	Dongyue	2018-05-08	add robust
html	44d3413	Dongyue	2018-05-07	correct mu_t+E(u_t)
Rmd	b082c1b	Dongyue	2018-05-07	correct mu_t+E(u_t)
Rmd	ee44935	Dongyue	2018-05-06	unknown sigma version
html	767077f	Dongyue	2018-05-06	unknown sigma version
html	341e471	Dongyue	2018-05-05	edit
html	c72247b	Dongyue	2018-05-05	edit
Rmd	3bd6a61	Dongyue	2018-05-05	first commit
html	ca322e8	Dongyue	2018-05-05	first commit
Rmd	b7e89a3	DongyueXie	2018-05-01	Start workflowr project.

Project Overview

This project aims to study a generalization version of normal version of smash. It is a version of wavelet denoising for Gaussian where each observation has additional known measurement error. The method is expected to handle the Poisson nugget effect.

I have created a R package for the functions used in the analysis.

Analysis

Intial investigation

Basic review
Poisson nugget simulation: assume \(\sigma\) is known.
A robust version of smash-gen: set the highest resolution wavelet coeffs to 0.
Treat Poisson data as normal: only do 1 iteration.
Expanding around ash posterior mean: iterate once but the Taylor series expansion is around ash posterior mean(applying ash to Poisson data first).

Estimate nugget effect

Poisson data with unknown nugget effect

Binomial data with unknown nugget effect

Smoothing with covariates

Credits

This project is based on the ideas from Professor Matthew Stephens. Thanks to Matthew Stephens and Kushal K Dey for their great help.

This reproducible R Markdown analysis was created with workflowr 1.0.1

Smash-gen