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The Friedman test is a non-parametric statistical test developed by Milton Friedman. [1] [2] [3] Similar to the parametric repeated measures ANOVA, it is used to detect differences in treatments across multiple test attempts. The procedure involves ranking each row (or block) together, then considering the values of ranks by columns.
The P program can be used for studies with dichotomous, continuous, or survival response measures. The user specifies the alternative hypothesis in terms of differing response rates, means, survival times, relative risks, or odds ratios.
NESSUS is a general-purpose, probabilistic analysis program that simulates variations and uncertainties in loads, geometry, material behavior and other user-defined inputs to compute probability of failure and probabilistic sensitivity measures of engineered systems. Because NESSUS uses highly efficient and accurate probabilistic analysis ...
Ooms, Marius (2009). "Trends in Applied Econometrics Software Development 1985–2008: An Analysis of Journal of Applied Econometrics Research Articles, Software Reviews, Data and Code". Palgrave Handbook of Econometrics. Vol. 2: Applied Econometrics. Palgrave Macmillan. pp. 1321– 1348. ISBN 978-1-4039-1800-0. Renfro, Charles G. (2004).
Not free (commercial), Free (non-commercial) Proprietary: A modern dialect of APL, enhanced with features for functional and object-oriented programming. Euler Math Toolbox: René Grothmann 1987 1988 2022-02-10 10 February 2022: Free GPL: Also a computer algebra system through interface with Maxima: Fityk: Marcin Wojdyr 2002 1.3.1 19 December 2016
The term non-parametric is not meant to imply that such models completely lack parameters but that the number and nature of the parameters are flexible and not fixed in advance. A histogram is a simple nonparametric estimate of a probability distribution. Kernel density estimation is another method to estimate a probability distribution.
A special case is use of non-parametric approaches. Furthermore, estimation in limited or full Bayesian frameworks is performed using the Metropolis-Hastings or the NUTS algorithms. [2] Some software solutions focus on a single estimation method, others cover a range of estimation methods and/or with interfaces for specific use cases.
An estimate of the uncertainty in the first and second case can be obtained with the binomial probability distribution using for example the probability of exceedance Pe (i.e. the chance that the event X is larger than a reference value Xr of X) and the probability of non-exceedance Pn (i.e. the chance that the event X is smaller than or equal ...