topic Confidence and prediction intervals for orthogonal regression? in Discussions

Confidence and prediction intervals for orthogonal regression?

JesperJohansen — Fri, 05 May 2017 08:58:01 GMT

I can tell that this question was posted back in 2012, but never answered, so here it goes again:

Is there a way to plot confidence and prediction intervals for orthogonal regression in the Bivariate platform. Also I would like to save the interval equations. Both options exist for "Fit line", i.e. OLS linear regression.

If the option does not exist, I would like to request it be implementet.

Re: Confidence and prediction intervals for orthogonal regression?

JesperJohansen — Thu, 13 Jul 2017 09:22:27 GMT

Noone from JMP reading this?

Re: Confidence and prediction intervals for orthogonal regression?

ian_jmp — Thu, 13 Jul 2017 10:08:08 GMT

With JMP Pro, you could try bootstrapping:

NamesDefaultToHere(1);

// Sample data
dt = NewTable("Orthogonal Regression",
		NewColumn("x1", Formula(RandomUniform(-1, 1))),
		NewColumn("x2", Formula(RandomUniform(-1, 1))),
		AddRows(50)
);

// Fit orthogonal
fo = dt << Bivariate(Y( :x2 ), X( :x1 ), Fit Orthogonal( Equal Variances ));

// Bootstrap fitted parameters
dt2 = Report(fo)[TableBox(2)] << Bootstrap(1000);

// Look at the result
dt2 << Distribution(
				Continuous Distribution( Column( :Intercept ) ),
				Continuous Distribution( Column( :Slope ) ),
				SendToReport(
					Dispatch( {"Intercept"}, "Quantiles", OutlineBox, {Close( 1 )} ),
					Dispatch( {"Intercept"}, "Summary Statistics", OutlineBox, {Close( 1 )} ),
					Dispatch( {"Slope"}, "Quantiles", OutlineBox, {Close( 1 )} ),
					Dispatch( {"Slope"}, "Summary Statistics", OutlineBox, {Close( 1 )} )
				)
			);

Re: Confidence and prediction intervals for orthogonal regression?

JesperJohansen — Thu, 03 Aug 2017 06:50:43 GMT

Alas, I don't have Pro :'-(

Re: Confidence and prediction intervals for orthogonal regression?

akrantasiwakoti — Thu, 10 Aug 2017 19:35:36 GMT

Hi Ian,

Thank you for this JSL script. However, the script only boostraps estimates of slope and intercept. I was curious how would I then go about estimating prediction interval in deming regression using this output? I would appreciate any assistance.

Thank you