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PARAMETERS OF THE DISTRIBUTION OF A RANDOM VARIABLE
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arbitrary assumption Bernoulli scheme binomial distribution bution called characteristic function coefficient compute condition constant continuous type defective items defined Definition degrees of freedom density function discrete type distri distribution function F(x efficient estimate elementary events elements empirical distribution function equals equation example exists expected value finite number follows formula gamma distribution hence hypothesis H0 independent random variables inequality integral interval investigation Kolmogorov large numbers law of large Let us consider Let us denote limit distribution Markov chain Markov process normal distribution observed value obtain parameter Q Poisson distribution population probability function probability theory Problem proof Prove random event random variables Xk random vector reject H0 respectively right-hand side Section Show simple sample standard deviation stationary stationary process statistic stochastic process stochastically convergent Suppose tables test the hypothesis unbiased estimate unknown parameter variance zero