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Given a function of the form y=a+blnx, (1) the coefficients can be found from least squares fitting as b = ...
Given a function of the form y=Ax^B, (1) least squares fitting gives the coefficients as b = ...
A method of displaying simple statistical parameters including hinges, the statistical median, and upper and lower values.
Random walk trajectories which are composed of self-similar jumps. They are described by the Lévy distribution.
L=sigma/(sigma_B), where sigma is the variance in a set of s Lexis trials and sigma_B is the variance assuming Bernoulli trials. If L<1, the trials are said to be subnormal, ...
A method for testing nested hypotheses. To apply the procedure, given a specific model, calculate the likelihood of observing the actual data. Then compare this likelihood to ...
Data resulting from the observation of a population on a number of variables over time. Whenever observations are made more than once, the data is considered to be ...
A robust estimation based on maximum likelihood arguments.
A random process whose future probabilities are determined by its most recent values. A stochastic process x(t) is called Markov if for every n and t_1<t_2...<t_n, we have ...
A sequence X_1, X_2, ... of random variates is called Markov (or Markoff) if, for any n, F(X_n|X_(n-1),X_(n-2),...,X_1)=F(X_n|X_(n-1)), i.e., if the conditional distribution ...
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