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Command-Line options
Compression:
C++: ./compress -f myfile.txt [-o myfile.hzip -s
Java: sh compress.sh -f myfile.txt [-o myfile.hzip -s]
Decompression:
C++: ./decompress -f myfile.hzip[-r -v]
Java: sh decompress.sh -f myfile.hzip [-o myfile.txt -s]
The command-line options that are within the square bracket are optional. The option \-f" precedes the input le name, which always has a .txt extension. The \-s" option prints statistics, such as for compression it prints, how many distinct characters are there, what is the compression ratio, and the wall clock time that it took for performing the compression task. For decompression, it prints how many character were written, and the wall clock time it took for performing the decompression task. The \-o" option precedes the name of an output le. If the output file name is not given, then we will append .hzip at the end of the input filename to create the output filename.
A value related with the square matrix which represents sums and products of its elements. For instance, if the matrix is then the determinant of A (conventionally written as
What is a Generalized Linear Model? A traditional linear model is of the form where Yi is the response variable for the ith observation, xi is a column vector of explanator
McNemar's test is the test for comparing proportions in data involving the paired samples. The test statistic can be given by it is most useful when the data have a symmetri
Non-identified response is a term used to signify censored observations in survival data, which are not independent of the endpoint of the interest. Such observations can happen f
Ignorability : The missing data mechanism is said to be ignorable for likelihood inference if (1) the joint likelihood for the responses of the interest and missing data indicators
Outlier is an observation which seems to deviate markedly from the other members of the sample in which it happens. In the set of systolic blood pressures, {125, 128, 130, 131, 19
t distribution
Non linear model : A model which is non-linear in the parameters, for instance are Some such type of models can be converted into the linear models by linearization (the s
The theorem relating structure of the likelihood to the concept of the sufficient statistic. Officially the necessary and sufficient condition which a statistic S be sufficient for
K-means cluster analysis is the method of cluster analysis in which from an initial partition of observations into K clusters, each observation in turn is analysed and reassigned,
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