Search results
Results from the WOW.Com Content Network
The p-value for the permutation test is the proportion of the r values generated in step (2) that are larger than the Pearson correlation coefficient that was calculated from the original data. Here "larger" can mean either that the value is larger in magnitude, or larger in signed value, depending on whether a two-sided or one-sided test is ...
The distance between the two distributions is calculated as the earth mover's distance or the Wasserstein distance between the two Gaussian distributions. Rather than directly comparing images pixel by pixel (for example, as done by the L2 norm ), the FID compares the mean and standard deviation of the deepest layer in Inception v3 (the 2048 ...
In time series analysis and statistics, the cross-correlation of a pair of random process is the correlation between values of the processes at different times, as a function of the two times. Let ( X t , Y t ) {\displaystyle (X_{t},Y_{t})} be a pair of random processes, and t {\displaystyle t} be any point in time ( t {\displaystyle t} may be ...
Principles of Model Checking is a textbook on model checking, an area of computer science that automates the problem of determining if a machine meets specification requirements. It was written by Christel Baier and Joost-Pieter Katoen , and published in 2008 by MIT Press .
Prefix sums are trivial to compute in sequential models of computation, by using the formula y i = y i − 1 + x i to compute each output value in sequence order. However, despite their ease of computation, prefix sums are a useful primitive in certain algorithms such as counting sort, [1] [2] and they form the basis of the scan higher-order function in functional programming languages.
A random arrangement of square colors would give Moran's I a value that is close to 0. In statistics, Moran's I is a measure of spatial autocorrelation developed by Patrick Alfred Pierce Moran . [ 1 ] [ 2 ] Spatial autocorrelation is characterized by a correlation in a signal among nearby locations in space.
The Bayes factor is a ratio of two competing statistical models represented by their evidence, and is used to quantify the support for one model over the other. [1] The models in question can have a common set of parameters, such as a null hypothesis and an alternative, but this is not necessary; for instance, it could also be a non-linear model compared to its linear approximation.
We then have three options: (1) gather more data, in the hope that this will allow clearly distinguishing between the first two models; (2) simply conclude that the data is insufficient to support selecting one model from among the first two; (3) take a weighted average of the first two models, with weights proportional to 1 and 0.368 ...