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  2. Dependent and independent variables - Wikipedia

    en.wikipedia.org/wiki/Dependent_and_independent...

    In mathematics, a function is a rule for taking an input (in the simplest case, a number or set of numbers) [5] and providing an output (which may also be a number). [5] A symbol that stands for an arbitrary input is called an independent variable, while a symbol that stands for an arbitrary output is called a dependent variable. [6]

  3. Density dependence - Wikipedia

    en.wikipedia.org/wiki/Density_dependence

    Density-dependent fecundity. Density-dependent fecundity exists, where the birth rate falls as competition increases. In the context of gastrointestinal nematodes, the weight of female Ascaris lumbricoides and its rates of egg production decrease as host infection intensity increases. Thus, the per-capita contribution of each worm to ...

  4. Independent and identically distributed random variables

    en.wikipedia.org/wiki/Independent_and...

    For example, repeated throws of loaded dice will produce a sequence that is i.i.d., despite the outcomes being biased. In signal processing and image processing, the notion of transformation to i.i.d. implies two specifications, the "i.d." part and the "i." part: i.d. – The signal level must be balanced on the time axis. i.

  5. Probability density function - Wikipedia

    en.wikipedia.org/wiki/Probability_density_function

    In probability theory, a probability density function (PDF), density function, or density of an absolutely continuous random variable, is a function whose value at any given sample (or point) in the sample space (the set of possible values taken by the random variable) can be interpreted as providing a relative likelihood that the value of the ...

  6. Multivariate t-distribution - Wikipedia

    en.wikipedia.org/wiki/Multivariate_t-distribution

    One common method of construction of a multivariate t-distribution, for the case of dimensions, is based on the observation that if and are independent and distributed as (,) and (i.e. multivariate normal and chi-squared distributions) respectively, the matrix is a p × p matrix, and is a constant vector then the random variable = / / + has the density [1]

  7. Beverton–Holt model - Wikipedia

    en.wikipedia.org/wiki/Beverton–Holt_model

    The Beverton–Holt model is a classic discrete-time population model which gives the expected number n t+1 (or density) of individuals in generation t + 1 as a function of the number of individuals in the previous generation, + = + /.

  8. Population dynamics - Wikipedia

    en.wikipedia.org/wiki/Population_dynamics

    The rate at which a population increases in size if there are no density-dependent forces regulating the population is known as the intrinsic rate of increase. It is d N d t = r N {\displaystyle {\mathrm {d} N \over \mathrm {d} t}=rN} where the derivative d N / d t {\displaystyle dN/dt} is the rate of increase of the population, N is the ...

  9. Copula (statistics) - Wikipedia

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

    A copula model has been developed in the field of oncology, for example, to jointly model genotypes, phenotypes, and pathways to reconstruct a cellular network to identify interactions between specific phenotype and multiple molecular features (e.g. mutations and gene expression change).