Run Bivariate and Export Predicteds to Vector

a_betancourt

All-

 

I want to run a script that runs a bivariate fit and save the predicteds to a vector. Also I want to avoid showing the bivariate window.

I am going to use the predicteds in additional computation and I don't want to save them to the data table.

 

Here is what I have so far and it is not working:

dt = Current Data Table();

kernelSmoother = Bivariate( Y( :Gas Rate ), X( :Days ), Kernel Smoother( 1, 1, 0.1, 4 ) );

data = kernelSmoother << curve[1] << Get values;

kernelSmoother << Close();

 Please help me with this issue.

Thanks.

-Alvaro

Thierry_S

Hi Alvaro,

Here is a functional option to achieve your goal but it uses the "Save Predicts" command to create a column that is delete at the end of the script: not the most elegant way to code but it works

Names Default to Here (1);

dt = New Table( "SMOOTHER",  //DUMMY TABLE
	Add Rows( 100 ),
	New Column( "X",
		Numeric,
		"Continuous",
		Format( "Best", 12 ),
		Set Values(
			[1.67141067952957, -0.76185849552488, -0.603569458585827,
			-0.756591674648757, 1.67340127655787, 0.0724575048740926,
			0.159151730633123, -0.142889975446617, -0.874252989365011,
			2.20294936082557, 0.18772074392043, -1.95789244934657,
			0.0565106299651629, -0.605593026877751, 0.215613648250195,
			2.3340049358012, -1.45888459127005, 0.583985564786941,
			-0.317617101142023, -1.01947851069745, -0.700371328441461,
			-1.76311244328458, 1.27998808300495, -1.04925859492911,
			0.0615589538740275, 0.462341043767196, -0.364022756931157,
			1.02591441155842, -0.961981489749384, -1.39888051775824,
			-0.865484355080553, 0.0575924079013767, 2.67743272934693,
			0.4895074706041, -0.353930652223919, 1.20197971417602, -1.94239723119073,
			-1.80497764170637, 0.25322439936394, -0.803259183745682,
			0.39877828050007, -1.39955079023924, -0.563270821962345,
			1.00706367759649, -0.920919695429428, 0.595171257889085,
			-0.785001186597782, 0.208610084917619, -1.365985295334, 1.3245192372372,
			-1.137335505516, 0.380940775706916, 0.20277798167723, 2.7906587946415,
			-0.474281058783615, 0.83128552480405, 1.06220976388948, -1.0783438678021,
			-0.328722058193142, -1.22317459147617, 0.333615959204505,
			-0.724960155164842, -2.10379798294336, 1.25945379498795,
			1.39315374582064, 0.555402221964133, 0.0260943614927882,
			-1.26262871377769, 0.905999353008783, -1.22971363040978,
			-0.0835673126007406, 1.15329782793192, -1.31994532927163,
			-1.09423235562862, 0.917365400223469, 1.65907130186835,
			-1.61042285504848, -0.591548656921071, 0.131205378825393,
			0.032797267621596, 0.87921466697569, 2.0586778387245, 0.562803054567428,
			0.615792486119142, -0.118419312940292, -1.04518110416241,
			-0.787515369931859, -0.627189651196433, 2.15324102656227,
			0.83620623786038, -0.012097864616955, -0.311798951269388,
			-2.59148801545045, 1.04832591823423, -0.586188226264991,
			0.939584870287117, -0.545152048029061, -0.475765043667705,
			-0.732494093426154, 0.926602866805675]
		)
	),
	New Column( "Y",
		Numeric,
		"Continuous",
		Format( "Best", 12 ),
		Formula( Sine( :X ) ),
		Set Selected
	)
);

biv = Bivariate( Y( :Y ), X( :X ), invisible); //Set the basic bivariate plot in invisible mode

biv << Kernel Smoother( 1, 1, 0.1, 4 , {Save predicteds});  // calls the Smoother with the option to save predicted

biv << Close window; 

vect = [];

vect = Column (dt, "Predicted Y") << get values; //captures the predicted Y into a list

Show (vect);

dt << Delete Columns (:Predicted Y); //removes the Predicted Y column

Maybe other JMP Forum members will have a more elegant way to get this done.

Best,

TS