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Stata allows for flexibility with assigning data types to data. Its compress command automatically reassigns data to data types that take up less memory without loss of information. Stata utilizes integer storage types which occupy only one or two bytes rather than four, and single-precision (4 bytes) rather than double-precision (8 bytes) is ...
The term block code may also refer to any error-correcting code that acts on a block of bits of input data to produce bits of output data (,). Consequently, the block coder is a memoryless device. Under this definition codes such as turbo codes , terminated convolutional codes and other iteratively decodable codes (turbo-like codes) would also ...
Initially, erasure codes were used to reduce the cost of storing "cold" (rarely-accessed) data efficiently; but erasure codes can also be used to improve performance serving "hot" (more-frequently-accessed) data. [12] RAID N+M divides data blocks across N+M drives, and can recover all the data when any M drives fail. [1]
In R, the packages sandwich [6] and plm [12] include a function for the Newey–West estimator. In Stata, the command newey produces Newey–West standard errors for coefficients estimated by OLS regression. [13] In MATLAB, the command hac in the Econometrics toolbox produces the Newey–West estimator (among others). [14]
A second common application of non-breaking spaces is in plain text file formats such as SGML, HTML, TeX and LaTeX, whose rendering engines are programmed to treat sequences of whitespace characters (space, newline, tab, form feed, etc.) as if they were a single character (but this behavior can be overridden).
A whitespace character is a character data element that represents white space when text is rendered for display by a computer. For example, a space character (U+0020 SPACE, ASCII 32) represents blank space such as a word divider in a Western script. A printable character results in output when rendered, but a whitespace character does not ...
Segmented regression, also known as piecewise regression or broken-stick regression, is a method in regression analysis in which the independent variable is partitioned into intervals and a separate line segment is fit to each interval.
The tslearn Python library implements DTW in the time-series context. The cuTWED CUDA Python library implements a state of the art improved Time Warp Edit Distance using only linear memory with phenomenal speedups. DynamicAxisWarping.jl Is a Julia implementation of DTW and related algorithms such as FastDTW, SoftDTW, GeneralDTW and DTW barycenters.