Transcription of 6 Probability Density Functions (PDFs)
{{id}} {{{paragraph}}}
Example: bankruptcy
6 Probability Density Functions (PDFs)
CSC 411 / CSC D11 / CSC C11 Probability Density Functions (PDFs) 6 probability density functions (PDFs)In many cases, we wish to handle data that can be represented as a real-valued random variable,or a real-valued vectorx= [x1, x2, .., xn]T. Most of the intuitions from discrete variables transferdirectly to the continuous case, although there are some describe the probabilities of a real-valued scalar variablexwith a Probability DensityFunction (PDF), writtenp(x). Any real-valued functionp(x)that satisfies:p(x) 0for allx(1) p(x)dx= 1(2)is a valid PDF.
CSC 411 / CSC D11 / CSC C11 Probability Density Functions (PDFs) The off-diagonal terms are covariances: Σ ij = cov(x i,x j) = E p(x)[(x i −µ i)(x j −µ j)] (10) between variables x i and x j.If the covariance is a large positive number, then we expect x
Loading..
Tags:
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document: