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  2. Frequency (statistics) - Wikipedia

    en.wikipedia.org/wiki/Frequency_(statistics)

    In statistics, the frequency or absolute frequency of an event is the number of times the observation has occurred/been recorded in an experiment or study. [ 1 ] : 12–19 These frequencies are often depicted graphically or tabular form.

  3. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    If the mean =, the first factor is 1, and the Fourier transform is, apart from a constant factor, a normal density on the frequency domain, with mean 0 and variance /. In particular, the standard normal distribution φ {\textstyle \varphi } is an eigenfunction of the Fourier transform.

  4. Delay spread - Wikipedia

    en.wikipedia.org/wiki/Delay_spread

    The correspondence with the frequency domain is the notion of coherence bandwidth (CB), which is the bandwidth over which the channel can be assumed flat (i.e. channel that passes all spectral components with approximately equal gain and linear phase.). Coherence bandwidth is related to the inverse of the delay spread.

  5. Analytic signal - Wikipedia

    en.wikipedia.org/wiki/Analytic_signal

    In mathematics and signal processing, an analytic signal is a complex-valued function that has no negative frequency components. [1] The real and imaginary parts of an analytic signal are real-valued functions related to each other by the Hilbert transform.

  6. Empirical distribution function - Wikipedia

    en.wikipedia.org/wiki/Empirical_distribution...

    In statistics, an empirical distribution function (commonly also called an empirical cumulative distribution function, eCDF) is the distribution function associated with the empirical measure of a sample. [1]

  7. Mean - Wikipedia

    en.wikipedia.org/wiki/Mean

    The arithmetic mean (or simply mean or average) of a list of numbers, is the sum of all of the numbers divided by their count.Similarly, the mean of a sample ,, …,, usually denoted by ¯, is the sum of the sampled values divided by the number of items in the sample.

  8. Logistic regression - Wikipedia

    en.wikipedia.org/wiki/Logistic_regression

    Logistic regression is used in various fields, including machine learning, most medical fields, and social sciences. For example, the Trauma and Injury Severity Score (), which is widely used to predict mortality in injured patients, was originally developed by Boyd et al. using logistic regression. [6]

  9. Mixed-data sampling - Wikipedia

    en.wikipedia.org/wiki/Mixed-data_sampling

    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.