Order statistics (1-4)

Statistics and distribution order

(A) setting ( X- . 1 , X- 2 , ... , X- n- ) is drawn from the overall X- ~ F. ( X ) of the sample, they are arranged in ascending order of X- (. 1) X- (2) ... X- ( n- ) , called X- (. 1) , X- (2) , ... , X- ( n- ) by sample X- . 1 , X- 2 , ... , X- n- green into order statistics , X- ( k ) , referred to as the first k th order statistics .
 
 
The maximum order statistic  X- ( n- ) = max { X- . 1 , X- 2 , ... , X- n- }
Minimum order statistic  X- (. 1) = min { X- . 1 , X- 2 , ... , X- n- } 
Range R & lt n- = X- ( n- ) - X- (. 1) 
 
Example :
      Observations 90,55,80,95,100 sorted 55,80,90,95,100
     Observations 80,90,69,80,90 sorted 69,80,80,90,90
 

Order statistics distribution function

Overall provided X distribution function is F. ( X ) , the minimum order statistic X (. 1) and the maximum order statistic X ( n- ) distribution functions are:

F_{1} = 1 - \left [ F_{\left ( x \right )} \right ] ^{n}

F_{n} = \left [ F_{\left ( x \right )} \right ] ^{n}

The overall probability density function statistics for continuous order

Provided the overall X probability density function F ( X ) , the minimum order statistic X (1) and the maximum order statistic X ( n- ) a probability density function are as follows:
 

f_{1} \left ( x \right )= nf\left ( x \right )\left [1 - F_{\left ( x \right )} \right ] ^{n - 1}

f_{1} \left ( x \right )= nf\left ( x \right ) \left [ F_{\left ( x \right )} \right ] ^{n-1}

 

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