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  2. State-space representation - Wikipedia

    en.wikipedia.org/wiki/State-space_representation

    The time variable can be continuous (e.g. ) or discrete (e.g. ). In the latter case, the time variable is usually used instead of . Hybrid systems allow for time domains that have both continuous and discrete parts. Depending on the assumptions made, the state-space model representation can assume the following forms:

  3. MATLAB - Wikipedia

    en.wikipedia.org/wiki/MATLAB

    MATLAB (an abbreviation of "MATrix LABoratory" [18]) 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.

  4. Gaussian process - Wikipedia

    en.wikipedia.org/wiki/Gaussian_process

    Using characteristic functions of random variables with denoting the imaginary unit such that =, the Gaussian property can be formulated as follows: {;} is Gaussian if and only if, for every finite set of indices , …,, there are real-valued , with > such that the following equality holds for all ,, …,,

  5. Matplotlib - Wikipedia

    en.wikipedia.org/wiki/Matplotlib

    Matplotlib (portmanteau of MATLAB, plot, and library [3]) is a plotting library for the Python programming language and its numerical mathematics extension NumPy.It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK.

  6. Comparison of programming languages (array) - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_programming...

    The following list contains syntax examples of how a range of element of an array can be accessed. In the following table: first – the index of the first element in the slice

  7. Poisson regression - Wikipedia

    en.wikipedia.org/wiki/Poisson_regression

    In statistics, Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. [1] Poisson regression assumes the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can be modeled by a linear combination of unknown parameters.

  8. Dirichlet distribution - Wikipedia

    en.wikipedia.org/wiki/Dirichlet_distribution

    Illustrating how the log of the density function changes when K = 3 as we change the vector α from α = (0.3, 0.3, 0.3) to (2.0, 2.0, 2.0), keeping all the individual 's equal to each other. The Dirichlet distribution of order K ≥ 2 with parameters α 1 , ..., α K > 0 has a probability density function with respect to Lebesgue measure on ...

  9. Zero-truncated Poisson distribution - Wikipedia

    en.wikipedia.org/wiki/Zero-truncated_Poisson...

    It is the conditional probability distribution of a Poisson-distributed random variable, given that the value of the random variable is not zero. Thus it is impossible for a ZTP random variable to be zero. Consider for example the random variable of the number of items in a shopper's basket at a supermarket checkout line.