Computational Methods in Statistics and Econometrics by Thomas R. Cundari

By Thomas R. Cundari

Highlights Monte Carlo and nonparametric statistical equipment for versions, simulations, analyses, and interpretations of statistical and econometric info. positive factors sensible functions.

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The function /(*,) represents the probability in the case where X takes *,-. , where f(xi) is called the probability function of X. More formally, the function f(xi) which has the following properties is defined as the probability function. 4. 2. 2 (Section 1 . 1 . 1 ), all the possible values of X are 0, 1,2 and 3. (note that X denotes the number of heads when a die is cast three times). That is, x\ = 0, jc2 = 1, Jt3 = 2 and x$ = 3 are assigned in this case. Y = 1) and P(X = 2), note that each sample point is mutually exclusive.

Therefore, A is not independent of C. As for C and D, since we have P(C) = 1 /2, P(D) = 1 /2 and P(C n D) = 1 /4, we can show that C is independent of D. 1 Univariate Random Variable and Distribution The random variable X is defined as the real value function on sample space Q. Since X is a function of a sample point tj, it is written as X = X(a>). Suppose that X(a>) takes a real value on the interval 7. , {«; X(w) € /}, which is simply written as {X e /}. 1), suppose that X is a random variable which takes the number of spots up on the die.

X, ~ N(ji, a2). Let us define fi = ^"-^aiXi, where a,, i = 1,2, • • • , « , are assumed to be known. 8 (p. 9 (p. 23), it is shown that the momentgenerating function of X is given by: (f>x(G) = exp(jU0 + jcr2^2), when X is normally distributed as X ~ N(/j, a1). Let fa be the moment-generating function of /}. > where n and cr2 in (f>x(ff) is simply replaced by // 2"=1 a/ and cr2 £"=] a2 in 0^(0), respectively. Moreover, note as follows. , when ft = X is taken, ft = X is normally distributed as: X ~ N(JJ, a2In).

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