[[talk-data]]

Notes

selective inference and selective inference (PNAS paper)

Goal: localize non-null regions (instead of rejecting as many alternatives as possible).

• Look at peaks (vs points or clusters) in data
• "topological features" of data landscape or "summary statistics"
  Construct confidence ellipsoids for peak locations

1. Select and detect regions. Pre-threshhold effect for candidates. Statistical test for significance among the survivors
2. Infer: produce confidence ellipsoid for the region + a confidence interval for the height of the selected peaks

Testing for significance requires some nuance. Math I didn't fully pay attantion to. Need to condition on an event that a point is selected as a potential peak in the first place.

Punchline: significant peaks consistently estimate true nes with ${\epsilon }_n$ convergence.

Mentions

const modules = await cJS()

const COLUMNS = [  
	{ id: "Name", value: page => page.$link },  
	{ id: "Last Modified", value: page => modules.dateTime.getLastMod(page) },
];  
  
return function View() {  
	const current = dc.useCurrentFile();
// Selecting `#game` pages, for example. 
	let queryString = `@page and linksto(${current.$link})`;
	let pages = dc.useQuery(queryString);
	
	// check types
	pages = pages.filter( (p) => !modules.typeCheck.checkAll(p, current) ).sort()
	
	
	return <dc.Table columns={COLUMNS} rows={pages} paging={20}/>;  
}  

const { dateTime } = await cJS()

return function View() {
	const file = dc.useCurrentFile();
	return <p class="dv-modified">Created {dateTime.getCreated(file)}     ֍     Last Modified {dateTime.getLastMod(file)}</p>
}