Вид для печати
Кто-нибудь знает статистический пакет, который умеет на основании данных подбирать методом наибольшего правдоподобия параметры для распределения Леви — Хинчина (иногда его еще называют обобщенным стабильным распределением, или Lévy skew alpha-stable distribution, или stable distribution). Или хотя бы считать плотность вероятности для данного распределения и кумулятивную функцию.
А Statistica или SPSS не пробовали?
А там это есть?Цитата:
Сообщение от Alexandra Radzivill
В статистике этого похоже нет: "DISTRIBUTION FITTING. The Distribution Fitting options allow the user to compare the distribution of a variable with a wide variety of theoretical distributions. You may fit to the data the Normal, Rectangular, Exponential, Gamma, Lognormal, Chi-square, Weibull, Gompertz, Binomial, Poisson, Geometric, or Bernoulli distribution. The fit can be evaluated via the Chi-square test or the Kolmogorov-Smirnov one-sample test (the fitting parameters can be controlled); the Lilliefors and Shapiro-Wilks' tests are also supported (see above). In addition, the fit of a particular hypothesized distribution to the empirical distribution can be evaluated in customized histograms (standard or cumulative) with overlaid selected functions; line and bar graphs of expected and observed frequencies, discrepancies and other results can be produced from the output Spreadsheets. Other distribution fitting options are available in STATISTICA Process Analysis, where the user can compute maximum-likelihood parameter estimates for the Beta, Exponential, Extreme Value (Type I, Gumbel), Gamma, Log-Normal, Rayleigh, and Weibull distributions. Also included in that module are options for automatically selecting and fitting the best distribution for the data, as well as options for general distribution fitting by moments (via Johnson and Pearson curves). User-defined 2- and 3-dimensional functions can also be plotted and overlaid on the graphs. The functions may reference a wide variety of distributions such as the Beta, Binomial, Cauchy, Chi-square, Exponential, Extreme value, F, Gamma, Geometric, Laplace, Logistic, Normal, Log-Normal, Pareto, Poisson, Rayleigh, t (Student), or Weibull distribution, as well as their integrals and inverses. Additional facilities to fit predefined or user-defined functions of practically unlimited complexity to the data are available in Nonlinear Estimation (available in STATISTICA Advanced Linear/Non-Linear Models)."
Самое близкое, что есть это распередление Коши, но даже обычного Lévy distribution нет:(
При SPSS не нашел соответсвующее описание. Может кто-нибудь из пользователей глянуть?