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JSL FIT 模型二因子響應曲面

早上好

我想為我的 JSL 實現一個具有“雙因素”的 FIT 模型回复表面模型”，

但我還沒有找到任何特定的 JSL 命令來執行此操作。

 

有人可以幫助我

 

這裡是我實現的代碼......但對於 FIT MODEL 部分來說是不完整的......

 

 

Clear Globals();
Clear Log();
Names Default To Here( 1 );
　
// code to choose among all opened tables which one will be selected for the analysis
OpenDT = List();
For( i = 1, i <= N Table(), i++,
 Insert Into( OpenDT, Data Table( i ) )
);
　
dlgDT = Dialog(
 "Please select Data Table for analysis",
 VList( selectDT = List Box( OpenDT ) ),
 HList( Button( "OK" ), Button( "Cancel" ) )
);

Show( dlgDT );

If( dlgDT["button"] == 1,
 Remove From( dlgDT, N Items( dlgDT ) );
 Eval List( dlgDT );
 
);
　
Current Data Table( selectDT[1] );

cd = Column Dialog(

 Var = collist( " select Response >>", MinCol( 1 ), MaxCol( 1 ) ),
 Hlist( "" ), 
 
 Ref = Collist( " Select Predictors >>", MinCol( 1 ) ),
 Hlist( "" ), 
 
 Hlist( "" ),
 mypareto = Check Box( " Show results's Pareto ", 1 ),
 Hlist( "Number of recursive trees -> ", forest = EditNumber( 10 ) ), 
 
 Vlist(
  mypareto = Check Box( " Show results's Pareto ", 1 ),
  Hlist( "" ),
  Hlist( "" ),
  Hlist( "select top predictors ", myrank = EditNumber( 5 ) ), 
 
 ), 
　
);
//);

//declaration of global variables
Response = cd["Var"]; //(Response Variable) ok
Predictor = cd["Ref"]; //(Predictor Variable) ok
Fsize = cd["forest"]; // number of tree to run
pareto = cd["mypareto"];
rank = cd["myrank"];

risultato = New Table( "Tree Table",
 Add Rows( 0 ),
 New Column( "Y", Character, "Nominal" ),
 New Column( "Term", Character, "Nominal", Set Property( "ID Column", 1 ) ),
 New Column( "Number of Splits", Numeric, "Continuous" ),
 New Column( "SS", Numeric, "Continuous" ),
 New Column( "SS 2", Character, "Nominal" ),
 New Column( "Portion", Numeric, "Continuous" ),

);

tree = Expr(
 partitioning = Partition(
  Y( Response( 1 ) ),
  X( Eval( Predictor ) ),
  Split History( 1 ),
  Informative Missing( 1 ),
  Validation Portion( 0.33 ),
  Minimun Size Split( 5 ),
  Column Contributions( 1 ), 
 
  Go
 );
　
 part = Report( partitioning )["Column Contributions"][Table Box( 1 )] <<
 Make Combined Data Table;
 part << select where( :Number of Splits == 0 );
 part << delete rows;
 partitioning << close window();
 part << set name( "Parts" );
 
 risultato = Data Table( risultato ) << Concatenate(
  Data Table( part ),
  Append to first table
 );
 Close( part, "no save" );
 
);
　
For( i = 1, i <= Fsize, i++,
 Current Data Table( selectDT[1] );
 
 tree;
);
　
If( Pareto == 1,
 Current Data Table( risultato );
 Pareto Plot(
 
  Cause( :Term ), 

 );
);
　
//create Ranking Table
　
Summary_Rank = Data Table( risultato ) << Summary(
 
 Group( :Term ),
 output table name( "Bootstrap Ranking" ), 
 
);
　
Data Table( Summary_Rank ) << Sort(
 
 By( :N Rows ),
 Order( Descending ),
 replace Table, 

);
　
x = N Rows( Summary_Rank );
 
Data Table( Summary_Rank ) << New Column( "Rank", numeric, , formula( Sequence( 1, x, 1 ) ) );
 
Data Table( Summary_Rank ) << select where( :Rank <= rank );
Column( 1 ) << set selected( 1 );
　
tempDt = Summary_Rank << Subset( columns( :Term ) );
Column( 1 ) << set selected( 1 );
　
predictor = Column( 1 ) << get values();
Close( tempDt, "no save" );
　
// declaration VarExpr variable
varExpr = {};
　
//------------------------------------------------FIT MODEL Two Factore Response Surface -------------------//
// parse word '& RS' into predictors variablee
For( i = 1, i <= N Items( predictor ), i++,
 Insert Into( varExpr, Parse( ":Name(\!"" || predictor[i] || "\!")" || Char( "& RS" ) ) )
);
　
Current Data Table( selectDT[1] );

FIT_MODEL = Fit Model(
 Y( Response( 1 ) ),
 Effects(
  (Eval( varExpr )), 
 
 ),
 Personality( "Standard Least Squares" ),
 Emphasis( "Effect Leverage" ), 
 
 Run( Profiler( 1, Confidence Intervals( 1 ), Arrange in Rows( 6 ), ), Show VIF( 1 ) )
);
 
FIT_MODEL;

 

 

 

回复：JSL FIT 模型雙因子響應曲面太棒了！！！，謝謝吉姆
回复：JSL FIT 模型雙因子響應曲面

我認為使用下面的示例可以解決您的要求：

predictor = {"X1","X2","X3","X4"};
varExpr = {};
// parse word '& RS' into predictors variablee
For( i = 1, i <= N Items( predictor ), i++,
 Insert Into( varExpr, Parse( ":Name(\!"" || predictor[i] || "\!")" || Char( "& RS" ) ) )
);


For( i = 1, i <= N Items( predictor ), i++,
 For( k = i, k <= N Items( predictor ), k++,
　  Insert Into( varExpr, Parse( ":Name(\!"" || predictor[i] || "\!")" || Char( " * " ) || ":Name(\!"" || predictor[k] || "\!")" ) )
))

回复：JSL FIT 模型雙因子響應曲面

JMP 的最佳腳本編寫器是 JMP 本身。 正如 Jim 所說，以交互方式構建您的模型，然後使用紅色三角形保存腳本。 它向您展示了它需要如何出現在您的 JSL 腳本中：

擬合模型(
Y( :Y ),
影響（
:X1 & RS,
:X2 & RS,
:X3 & RS,
:X4 & RS,
:X1 * :X1,
:X1 * :X2,
:X2 * :X2,
:X1 * :X3,
:X2 * :X3,
:X3 * :X3,
:X1 * :X4,
:X2 * :X4,
:X3 * :X4,
:X4 * :X4
),
個性（“標準最小二乘法”）
);

回复：JSL FIT 模型雙因子響應曲面

謝謝你吉姆的回答，

似乎沒有一種快速的方法來影響響應麵條件：（如下例）

 

X1 RS
X2 RS
X3 RS
X4 RS
X1*X1
X1*X2
X1*X3
X1*X4
X2*X2
X2*X3
X2*X4
X3*X3
X3*X4
X4*X4

 

通過我的腳本，我能夠創建 X1 RS、X2 RS、X3 RS、X4 RS，

但現在我需要通過單獨的腳本創建乘法因子......

回复：JSL FIT 模型雙因子響應曲面

您可以在“擬合線性模型”一書中找到雙因子響應曲面模型的一個很好的例子：

幫助==>書籍==>擬合線性模型

以交互方式生成模型後，您可以從輸出顯示中的紅色三角形請求“保存腳本”。它將為您提供運行分析所需的 JSL。