The Lognormal Distribution Function is characterized by 2 parameters which are the Scale and the Shape. This distribution is usually used to model Faulure Times where aging is the most dominant cause of failure. Here is a JMP JSL script that demonstrates how the Lognormal distribution changes as each of these parameters change.
The JMP JSL Script is shown below
Clear Globals(); Shap = 2; Scal = 4; PDF_fx = Expr( Exp( -(Log( x ) - Log( Scal )) ^ 2 / (2 * Shap ^ 2) ) / (Shap * x * Sqrt( 2 * Pi() )) ); Log_Window = New Window( "Properties of the LogLogistic Density and Hazard Functions", V List Box( GraphWindow = Graph( FrameSize( 500, 500 ), Double Buffer, FrameSize( 500, 300 ), X Scale( 0, 3 ), Y Scale( 0, 1 ), Double Buffer, A = Scal; B = Shap; TEXT_MESSAGE = "; Scale parameter A = " || Char( A ) || "; Shape parameter B = " || Char( B ); NON_EXPO2 = Expr( Caption( TEXT_MESSAGE ) ); Pen Size( 2 ); Pen Color( "red" ); Text Color( "red" ); Text Size( 12 ); Text( {1, .7}, "LogNormal Probability Distribution Function" ); Y Function( PDF_fx, x ); ), H List Box( V List Box( H List Box( TB1 = Text Box( " Scale Parameter A" ), Text Box( " " ) ), Slider Box( 0.0001, 20, Scal, GraphWindow << reshow; Log_Window << reshow; A = Scal; B = Shap; TEXT_MESSAGE = "; Scale parameter A = " || Char( A ) || "; Shape parameter B = " || Char( B ); NON_EXPO2; ) ), V List Box( H List Box( TB2 = Text Box( " Shape Parameter B" ), Text Box( " " ) ), Slider Box( 0.0001, 10, Shap, GraphWindow << reshow; A = Scal; B = Shap; TEXT_MESSAGE = "; Scale parameter A = " || Char( A ) || "; Shape parameter B = " || Char( B ); NON_EXPO2; ) ) ) ) ); TB1 << Font color( "BLUE" ); TB1 << set Font size( 10 ); TB2 << Font color( "BLUE" ); TB2 << set Font size( 10 );
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