11/11/2023 0 Comments Matlab polytool assignment![]() ![]() %% = KSTEST(.) also returns the asymptotic P-value P.%% = KSTEST(.) also returns the K-S test statistic KSSTAT% defined above for the test type indicated by TAIL.%% = KSTEST(.) returns the critical value of the test CV.%% In general, the decision to reject the null hypothesis is based on the % critical value. % In this case, the interval along the x-axis (the column 1 spread of CDF)% must span the observations in X for successful interpolation. ![]() % When column 1 of CDF represents x-axis points independent of X, CDF is % 're-sampled' at the observations found in the vector X via interpolation. Since the K-S% test statistic will occur at one of the observations in X, the calculation % is most efficient when CDF is only specified at the observations in X. Column 1 contains the % x-axis data, column 2 the corresponding y-axis c.d.f data. If specified, it must be an % explicit 2-column matrix of paired (x,y) values. Missing observations in X, indicated by NaN's % (Not-a-Number), are ignored.%% CDF is the c.d.f. specified under the null hypothesis.% % Null Hypothesis: F(x) equal to CDF for all x.% For TAIL = 0 (2-sided test), alternative: F(x) not equal to CDF.% For TAIL = 1 (1-sided test), alternative: F(x) greater than CDF.% For TAIL = -1 (1-sided test), alternative: F(x) less than CDF.%% For TAIL = 0, 1, and -1, the K-S test statistics are T = max|S(x) - CDF|,% T = max, and T = max, respectively.%% X may be a row or column vector representing a random sample from some% underlying distribution. estimated from the sample vector X, F(x) % be the corresponding true (but unknown) population c.d.f., and CDF be the% known input c.d.f. H indicates the result of % the hypothesis test:% H = 0 => Do not reject the null hypothesis at significance level ALPHA.% H = 1 => Reject the null hypothesis at significance level ALPHA.% % Let S(x) be the empirical c.d.f. ALPHA and TAIL are optional % scalar inputs: ALPHA is the desired significance level (default = 0.05) % TAIL indicates the type of test (default = 0). ![]() CDF is optional: if omitted or % unspecified (i.e., set to an empty matrix ), the hypothetical c.d.f is % assumed to be a standard normal, N(0,1).
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