Search results
Results from the WOW.Com Content Network
Gretl has its own scripting language, called hansl (which is a recursive acronym for Hansl's A Neat Scripting Language).. Hansl is a Turing-complete, interpreted programming language, featuring loops, conditionals, user-defined functions and complex data structures. [8]
MATLAB (an abbreviation of "MATrix LABoratory" [22]) is a proprietary multi-paradigm programming language and numeric computing environment developed by MathWorks.MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages.
In Matlab/GNU Octave a matrix A can be vectorized by A(:). GNU Octave also allows vectorization and half-vectorization with vec(A) and vech(A) respectively. Julia has the vec(A) function as well. In Python NumPy arrays implement the flatten method, [note 1] while in R the desired effect can be achieved via the c() or as.vector() functions.
The effect of z-score normalization on k-means clustering. 4 gaussian clusters of points are generated, then squashed along the y-axis, and a = clustering was computed. . Without normalization, the clusters were arranged along the x-axis, since it is the axis with most of varia
Exponential smoothing or exponential moving average (EMA) is a rule of thumb technique for smoothing time series data using the exponential window function. Whereas in the simple moving average the past observations are weighted equally, exponential functions are used to assign exponentially decreasing weights over time. It is an easily learned ...
The numbers of the males, females, and right- and left-handed individuals are called marginal totals.The grand total (the total number of individuals represented in the contingency table) is the number in the bottom right corner.
Python has many different implementations of the spearman correlation statistic: it can be computed with the spearmanr function of the scipy.stats module, as well as with the DataFrame.corr(method='spearman') method from the pandas library, and the corr(x, y, method='spearman') function from the statistical package pingouin.
Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing.. The data is linearly transformed onto a new coordinate system such that the directions (principal components) capturing the largest variation in the data can be easily identified.