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The Burt table is the symmetric matrix of all two-way cross-tabulations between the categorical variables, and has an analogy to the covariance matrix of continuous variables. Analyzing the Burt table is a more natural generalization of simple correspondence analysis , and individuals or the means of groups of individuals can be added as ...
Loop fission (or loop distribution) is a compiler optimization in which a loop is broken into multiple loops over the same index range with each taking only a part of the original loop's body. [1] [2] The goal is to break down a large loop body into smaller ones to achieve better utilization of locality of reference.
t-distributed stochastic neighbor embedding (t-SNE) is a statistical method for visualizing high-dimensional data by giving each datapoint a location in a two or three-dimensional map. It is based on Stochastic Neighbor Embedding originally developed by Geoffrey Hinton and Sam Roweis, [ 1 ] where Laurens van der Maaten and Hinton proposed the t ...
The MIDAS can also be used for machine learning time series and panel data nowcasting. [6] [7] The machine learning MIDAS regressions involve Legendre polynomials.High-dimensional mixed frequency time series regressions involve certain data structures that once taken into account should improve the performance of unrestricted estimators in small samples.
where the last sum used another way to indicate that the index runs over the set [] = {, …,}. Then we proceed as follows: For each i ∈ [ n ] {\displaystyle i\in [n]} we compute the mean x ¯ ( i ) {\displaystyle {\bar {x}}_{(i)}} of the jackknife subsample consisting of all but the i {\displaystyle i} -th data point, and this is called the ...
In general, a distance matrix is a weighted adjacency matrix of some graph. In a network, a directed graph with weights assigned to the arcs, the distance between two nodes of the network can be defined as the minimum of the sums of the weights on the shortest paths joining the two nodes (where the number of steps in the path is bounded). [2]
For matrices in mathematical notation, the first index indicates the row, and the second indicates the column, e.g., given a matrix , the entry , is in its first row and second column. This convention is carried over to the syntax in programming languages, [ 2 ] although often with indexes starting at 0 instead of 1.
The design matrix has dimension n-by-p, where n is the number of samples observed, and p is the number of variables measured in all samples. [4] [5]In this representation different rows typically represent different repetitions of an experiment, while columns represent different types of data (say, the results from particular probes).