All Questions
Tagged with online-algorithms variance
8 questions
17
votes
2
answers
12k
views
What is the precise definition of a "Heywood Case"?
I had been using the term "Heywood Case" somewhat informally to refer to situations where an online, 'finite response' iteratively updated estimate of the variance became negative due to numerical ...
14
votes
3
answers
6k
views
Online estimation of variance with limited memory
I am creating a component that aims to calculate the average and variance of a metric associated with events happening during time but with a limited internal memory.
Imagine that the events are ...
5
votes
3
answers
5k
views
How do I compute/estimate the variance of sequential data? [duplicate]
Say I have a (infinite) sequences like 1, 3, 2, 2, 1, 3 ...
I want to estimate their mean and variance of the sequence at time $t$.
But I won't have enough storage to keep all the data seen ...
4
votes
0
answers
228
views
Prediction Intervals for Incremental OLS regression
I am implementing incremental OLS regression algorithm where the data points arrive one at a time. As the regression parameters are determined by the formula, $(X'X)^{-1} X'y$ and the Sherman-Morrison ...
3
votes
0
answers
610
views
Online algorithm to compute variance with a decay
Could somebody point me to an online algorithm that computes the variance, but gives a higher weight to more recent values?
2
votes
1
answer
73
views
What is the intuition behind the single-pass algorithm (Welford's method) for the corrected sum of squares?
The corrected sum of squares is the sum of squares of the deviations of a set of values about its mean.
$$
S = \sum_{i=1}^k\space\space(x_i - \bar x)^2
$$
We can calculate the mean in a streaming ...
2
votes
0
answers
872
views
Change in standard deviation when a value is removed
Let's say a list of numbers $L$ has standard deviation $S$. Is there a formula for finding $S$ if I remove an element $l$ from $L$? Assume we know the mean of both $L$ and $L - l$.
1
vote
1
answer
233
views
Estimate variance of sub-sets from overall variance
I am looking for a way to estimate the variance of a summed sub-set based on the variance of those sums.
Si = sum( Ai )
S = { S0...Sn }
V = variance( S )
That is,...