Title :
Distribution Laws of Small Size Samples. Metrological Implementation
Author :
Florescu, Radu ; Thirer, Nonel
Author_Institution :
Dept. of Electr. & Electron. Eng., ORT Braude Coll., Karmiel
Abstract :
In this paper is exposed an original technique to determine the empirical probability density function (pdf) and the empirical cumulative distribution function (cdf) and to estimate moments of any order, for a small size random sample (m=3 - 10) of a continuous random variable (rv). The efficiency of the proposed method is checked up by applying the Kolmogorov-Smirnov test to several series of pseudorandom numbers heaving known distribution laws. In the last part of the paper are presented the advantages of our method for distribution determination in metrological measurements, specially for destructive or expensive measurements.
Keywords :
measurement theory; probability; sampling methods; Kolmogorov-Smirnov test; continuous random variable; distribution laws; empirical cumulative distribution function; metrological implementation; probability density function; pseudorandom numbers; Biology computing; Data mining; Distributed computing; Distribution functions; Metrology; Phase frequency detector; Probability density function; Random variables; Statistical distributions; Testing; Consistent and unbiased estimators; Kolmogorov-Smirnov test; Metrological measurements; Pseudorandom numbers; Random small size sample;
Conference_Titel :
Electrical and Electronics Engineers in Israel, 2006 IEEE 24th Convention of
Conference_Location :
Eilat
Print_ISBN :
1-4244-0229-8
Electronic_ISBN :
1-4244-0230-1
DOI :
10.1109/EEEI.2006.321099
