Re: [R] Issues when trying to fit a nonlinear regression model
Thank you so much for your valuable feedback Berwin. Have a great day. Cheers, Paul El El dom, 20 de ago. de 2023 a la(s) 10:21 p. m., Berwin A Turlach < berwin.turl...@gmail.com> escribió: > G'day Paul, > > On Sun, 20 Aug 2023 12:15:08 -0500 > Paul Bernal wrote: > > > Any idea on how to proceed in this situation? What could I do? > > You are fitting a simple asymptotic model for which nls() can find good > starting values if you use the self starting models (SSxyz()). Well, > Doug (et al.) choose to parameterise the asymptotic model differently, > but you can easily change to your parameterisation if you want: > > ``` > fm1 <- nls(y ~ SSasymp(x, Asym, R0, lrc), data=mod14data2_random) > theta1 <- coef(fm1)["Asym"] > theta2 <- coef(fm1)["Asym"] - coef(fm1)["R0"] > theta3 <- exp(coef(fm1)["lrc"]) > > fm2 <- nls(y ~ theta1 - theta2 * exp(-theta3*x), >start=list(theta1=theta1, theta2=theta2, theta3=theta3), >data=mod14data2_random) > summary(fm2) > ``` > > Cheers, > > Berwin > [[alternative HTML version deleted]] __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Issues when trying to fit a nonlinear regression model
G'day Paul, On Sun, 20 Aug 2023 12:15:08 -0500 Paul Bernal wrote: > Any idea on how to proceed in this situation? What could I do? You are fitting a simple asymptotic model for which nls() can find good starting values if you use the self starting models (SSxyz()). Well, Doug (et al.) choose to parameterise the asymptotic model differently, but you can easily change to your parameterisation if you want: ``` fm1 <- nls(y ~ SSasymp(x, Asym, R0, lrc), data=mod14data2_random) theta1 <- coef(fm1)["Asym"] theta2 <- coef(fm1)["Asym"] - coef(fm1)["R0"] theta3 <- exp(coef(fm1)["lrc"]) fm2 <- nls(y ~ theta1 - theta2 * exp(-theta3*x), start=list(theta1=theta1, theta2=theta2, theta3=theta3), data=mod14data2_random) summary(fm2) ``` Cheers, Berwin __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Issues when trying to fit a nonlinear regression model
Thanks a lot Bert, I appreciate your help. Kind regards, Paul El El dom, 20 de ago. de 2023 a la(s) 2:39 p. m., Bert Gunter < bgunter.4...@gmail.com> escribió: > Basic algebra and exponentials/logs. I leave those details to you or > another HelpeR. > > -- Bert > > On Sun, Aug 20, 2023 at 12:17 PM Paul Bernal > wrote: > >> Dear Bert, >> >> Thank you for your extremely valuable feedback. Now, I just want to >> understand why the signs for those starting values, given the following: >> > #Fiting intermediate model to get starting values >> > intermediatemod <- lm(log(y - .37) ~ x, data=mod14data2_random) >> > summary(intermediatemod) >> >> Call: >> lm(formula = log(y - 0.37) ~ x, data = mod14data2_random) >> >> Residuals: >> Min 1Q Median 3Q Max >> -0.7946 -0.0908 0.0379 0. 0.5917 >> >> Coefficients: >> Estimate Std. Error t value Pr(>|t|) >> (Intercept) -1.816930.25806 -7.04 8.8e-06 *** >> x -0.055380.00964 -5.75 6.8e-05 *** >> --- >> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 >> >> Residual standard error: 0.323 on 13 degrees of freedom >> Multiple R-squared: 0.717, Adjusted R-squared: 0.696 >> F-statistic: 33 on 1 and 13 DF, p-value: 6.76e-05 >> >> Kind regards, >> Paul >> >> El dom, 20 ago 2023 a las 14:07, Bert Gunter () >> escribió: >> >>> Oh, sorry; I changed signs in the model, fitting >>> theta0 + theta1*exp(theta2*x) >>> >>> So for theta0 - theta1*exp(-theta2*x) use theta1= -.exp(-1.8) and theta2 >>> = +.055 as starting values. >>> >>> -- Bert >>> >>> >>> >>> >>> >>> On Sun, Aug 20, 2023 at 11:50 AM Paul Bernal >>> wrote: >>> Dear Bert, Thank you so much for your kind and valuable feedback. I tried finding the starting values using the approach you mentioned, then did the following to fit the nonlinear regression model: nlregmod2 <- nls(y ~ theta1 - theta2*exp(-theta3*x), start = list(theta1 = 0.37, theta2 = exp(-1.8), theta3 = -0.05538), data=mod14data2_random) However, I got this error: Error in nls(y ~ theta1 - theta2 * exp(-theta3 * x), start = list(theta1 = 0.37, : step factor 0.000488281 reduced below 'minFactor' of 0.000976562 nlregmod2 <- nlxb(y ~ theta1 - theta2*exp(-theta3*x), start = list(theta1 = 0.37, theta2 = exp(-1.8), theta3 = -0.05538), data=mod14data2_random) summary(nlregmod2) Object has try-error or missing parameters nlregmod2 And I get some NA values when retrieving the statistics for the fitted model: residual sumsquares = 0.0022973 on 15 observations after 2235Jacobian and 2861 function evaluations namecoeff SE tstat pval gradient JSingval theta1 9330.89NA NA NA 5.275e-11 967470 theta2 9330.41NA NA NA -5.318e-11 1.772 theta3 -3.0032e-07NA NA NA 1.389e-05 8.028e-12 Kind regards, Paul El dom, 20 ago 2023 a las 13:21, Bert Gunter () escribió: > I got starting values as follows: > Noting that the minimum data value is .38, I fit the linear model > log(y - .37) ~ x to get intercept = -1.8 and slope = -.055. So I used .37, > exp(-1.8) and -.055 as the starting values for theta0, theta1, and theta2 > in the nonlinear model. This converged without problems. > > Cheers, > Bert > > > On Sun, Aug 20, 2023 at 10:15 AM Paul Bernal > wrote: > >> Dear friends, >> >> This is the dataset I am currently working with: >> >dput(mod14data2_random) >> structure(list(index = c(14L, 27L, 37L, 33L, 34L, 16L, 7L, 1L, >> 39L, 36L, 40L, 19L, 28L, 38L, 32L), y = c(0.44, 0.4, 0.4, 0.4, >> 0.4, 0.43, 0.46, 0.49, 0.41, 0.41, 0.38, 0.42, 0.41, 0.4, 0.4 >> ), x = c(16, 24, 32, 30, 30, 16, 12, 8, 36, 32, 36, 20, 26, 34, >> 28)), row.names = c(NA, -15L), class = "data.frame") >> >> I did the following to try to fit a nonlinear regression model: >> >> #First, Procedure to Find Starting (initial) Values For Theta1, >> Theta2, and >> Theta3 >> >> mymod2 <- y ~ theta1 - theta2*exp(-theta3*x) >> >> strt2 <- c(theta1 = 1, theta2 = 2, theta3 = 3) >> >> trysol2<-nlxb(formula=mymod2, data=mod14data2_random, start=strt2, >> trace=TRUE) >> trysol2 >> trysol2$coefficients[[3]] >> >> #Fitting nonlinear Regression Model Using Starting Values From >> Previous Part >> nonlinearmod2 <- nls(mymod2, start = list(theta1 = >> trysol2$coefficients[[1]], >> theta2 = trysol2$coefficients[[2]],
Re: [R] Issues when trying to fit a nonlinear regression model
Basic algebra and exponentials/logs. I leave those details to you or another HelpeR. -- Bert On Sun, Aug 20, 2023 at 12:17 PM Paul Bernal wrote: > Dear Bert, > > Thank you for your extremely valuable feedback. Now, I just want to > understand why the signs for those starting values, given the following: > > #Fiting intermediate model to get starting values > > intermediatemod <- lm(log(y - .37) ~ x, data=mod14data2_random) > > summary(intermediatemod) > > Call: > lm(formula = log(y - 0.37) ~ x, data = mod14data2_random) > > Residuals: > Min 1Q Median 3Q Max > -0.7946 -0.0908 0.0379 0. 0.5917 > > Coefficients: > Estimate Std. Error t value Pr(>|t|) > (Intercept) -1.816930.25806 -7.04 8.8e-06 *** > x -0.055380.00964 -5.75 6.8e-05 *** > --- > Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 > > Residual standard error: 0.323 on 13 degrees of freedom > Multiple R-squared: 0.717, Adjusted R-squared: 0.696 > F-statistic: 33 on 1 and 13 DF, p-value: 6.76e-05 > > Kind regards, > Paul > > El dom, 20 ago 2023 a las 14:07, Bert Gunter () > escribió: > >> Oh, sorry; I changed signs in the model, fitting >> theta0 + theta1*exp(theta2*x) >> >> So for theta0 - theta1*exp(-theta2*x) use theta1= -.exp(-1.8) and theta2 >> = +.055 as starting values. >> >> -- Bert >> >> >> >> >> >> On Sun, Aug 20, 2023 at 11:50 AM Paul Bernal >> wrote: >> >>> Dear Bert, >>> >>> Thank you so much for your kind and valuable feedback. I tried finding >>> the starting values using the approach you mentioned, then did the >>> following to fit the nonlinear regression model: >>> nlregmod2 <- nls(y ~ theta1 - theta2*exp(-theta3*x), >>> start = >>> list(theta1 = 0.37, >>> theta2 = exp(-1.8), >>> theta3 = -0.05538), data=mod14data2_random) >>> However, I got this error: >>> Error in nls(y ~ theta1 - theta2 * exp(-theta3 * x), start = list(theta1 >>> = 0.37, : >>> step factor 0.000488281 reduced below 'minFactor' of 0.000976562 >>> nlregmod2 <- nlxb(y ~ theta1 - theta2*exp(-theta3*x), >>> start = >>> list(theta1 = 0.37, >>> theta2 = exp(-1.8), >>> theta3 = -0.05538), data=mod14data2_random) >>> summary(nlregmod2) >>> Object has try-error or missing parameters >>> nlregmod2 >>> And I get some NA values when retrieving the statistics for the fitted >>> model: >>> residual sumsquares = 0.0022973 on 15 observations >>> after 2235Jacobian and 2861 function evaluations >>> namecoeff SE tstat pval gradient >>>JSingval >>> theta1 9330.89NA NA NA 5.275e-11 >>> 967470 >>> theta2 9330.41NA NA NA -5.318e-11 >>> 1.772 >>> theta3 -3.0032e-07NA NA NA 1.389e-05 >>> 8.028e-12 >>> >>> Kind regards, >>> Paul >>> >>> >>> El dom, 20 ago 2023 a las 13:21, Bert Gunter () >>> escribió: >>> I got starting values as follows: Noting that the minimum data value is .38, I fit the linear model log(y - .37) ~ x to get intercept = -1.8 and slope = -.055. So I used .37, exp(-1.8) and -.055 as the starting values for theta0, theta1, and theta2 in the nonlinear model. This converged without problems. Cheers, Bert On Sun, Aug 20, 2023 at 10:15 AM Paul Bernal wrote: > Dear friends, > > This is the dataset I am currently working with: > >dput(mod14data2_random) > structure(list(index = c(14L, 27L, 37L, 33L, 34L, 16L, 7L, 1L, > 39L, 36L, 40L, 19L, 28L, 38L, 32L), y = c(0.44, 0.4, 0.4, 0.4, > 0.4, 0.43, 0.46, 0.49, 0.41, 0.41, 0.38, 0.42, 0.41, 0.4, 0.4 > ), x = c(16, 24, 32, 30, 30, 16, 12, 8, 36, 32, 36, 20, 26, 34, > 28)), row.names = c(NA, -15L), class = "data.frame") > > I did the following to try to fit a nonlinear regression model: > > #First, Procedure to Find Starting (initial) Values For Theta1, > Theta2, and > Theta3 > > mymod2 <- y ~ theta1 - theta2*exp(-theta3*x) > > strt2 <- c(theta1 = 1, theta2 = 2, theta3 = 3) > > trysol2<-nlxb(formula=mymod2, data=mod14data2_random, start=strt2, > trace=TRUE) > trysol2 > trysol2$coefficients[[3]] > > #Fitting nonlinear Regression Model Using Starting Values From > Previous Part > nonlinearmod2 <- nls(mymod2, start = list(theta1 = > trysol2$coefficients[[1]], > theta2 = trysol2$coefficients[[2]], > theta3 = trysol2$coefficients[[3]]), data = > mod14data2_random) > > And I got this error: > Error in nlsModel(formula, mf, start, wts, scaleOffset = scOff, > nDcentral = > nDcntr) : > singular gradient matrix at initial parameter estimates >
Re: [R] Issues when trying to fit a nonlinear regression model
Dear Bert, Thank you for your extremely valuable feedback. Now, I just want to understand why the signs for those starting values, given the following: > #Fiting intermediate model to get starting values > intermediatemod <- lm(log(y - .37) ~ x, data=mod14data2_random) > summary(intermediatemod) Call: lm(formula = log(y - 0.37) ~ x, data = mod14data2_random) Residuals: Min 1Q Median 3Q Max -0.7946 -0.0908 0.0379 0. 0.5917 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -1.816930.25806 -7.04 8.8e-06 *** x -0.055380.00964 -5.75 6.8e-05 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.323 on 13 degrees of freedom Multiple R-squared: 0.717, Adjusted R-squared: 0.696 F-statistic: 33 on 1 and 13 DF, p-value: 6.76e-05 Kind regards, Paul El dom, 20 ago 2023 a las 14:07, Bert Gunter () escribió: > Oh, sorry; I changed signs in the model, fitting > theta0 + theta1*exp(theta2*x) > > So for theta0 - theta1*exp(-theta2*x) use theta1= -.exp(-1.8) and theta2 = > +.055 as starting values. > > -- Bert > > > > > > On Sun, Aug 20, 2023 at 11:50 AM Paul Bernal > wrote: > >> Dear Bert, >> >> Thank you so much for your kind and valuable feedback. I tried finding >> the starting values using the approach you mentioned, then did the >> following to fit the nonlinear regression model: >> nlregmod2 <- nls(y ~ theta1 - theta2*exp(-theta3*x), >> start = >> list(theta1 = 0.37, >> theta2 = exp(-1.8), >> theta3 = -0.05538), data=mod14data2_random) >> However, I got this error: >> Error in nls(y ~ theta1 - theta2 * exp(-theta3 * x), start = list(theta1 >> = 0.37, : >> step factor 0.000488281 reduced below 'minFactor' of 0.000976562 >> nlregmod2 <- nlxb(y ~ theta1 - theta2*exp(-theta3*x), >> start = >> list(theta1 = 0.37, >> theta2 = exp(-1.8), >> theta3 = -0.05538), data=mod14data2_random) >> summary(nlregmod2) >> Object has try-error or missing parameters >> nlregmod2 >> And I get some NA values when retrieving the statistics for the fitted >> model: >> residual sumsquares = 0.0022973 on 15 observations >> after 2235Jacobian and 2861 function evaluations >> namecoeff SE tstat pval gradient >> JSingval >> theta1 9330.89NA NA NA 5.275e-11 >> 967470 >> theta2 9330.41NA NA NA -5.318e-11 >> 1.772 >> theta3 -3.0032e-07NA NA NA 1.389e-05 >> 8.028e-12 >> >> Kind regards, >> Paul >> >> >> El dom, 20 ago 2023 a las 13:21, Bert Gunter () >> escribió: >> >>> I got starting values as follows: >>> Noting that the minimum data value is .38, I fit the linear model log(y >>> - .37) ~ x to get intercept = -1.8 and slope = -.055. So I used .37, >>> exp(-1.8) and -.055 as the starting values for theta0, theta1, and theta2 >>> in the nonlinear model. This converged without problems. >>> >>> Cheers, >>> Bert >>> >>> >>> On Sun, Aug 20, 2023 at 10:15 AM Paul Bernal >>> wrote: >>> Dear friends, This is the dataset I am currently working with: >dput(mod14data2_random) structure(list(index = c(14L, 27L, 37L, 33L, 34L, 16L, 7L, 1L, 39L, 36L, 40L, 19L, 28L, 38L, 32L), y = c(0.44, 0.4, 0.4, 0.4, 0.4, 0.43, 0.46, 0.49, 0.41, 0.41, 0.38, 0.42, 0.41, 0.4, 0.4 ), x = c(16, 24, 32, 30, 30, 16, 12, 8, 36, 32, 36, 20, 26, 34, 28)), row.names = c(NA, -15L), class = "data.frame") I did the following to try to fit a nonlinear regression model: #First, Procedure to Find Starting (initial) Values For Theta1, Theta2, and Theta3 mymod2 <- y ~ theta1 - theta2*exp(-theta3*x) strt2 <- c(theta1 = 1, theta2 = 2, theta3 = 3) trysol2<-nlxb(formula=mymod2, data=mod14data2_random, start=strt2, trace=TRUE) trysol2 trysol2$coefficients[[3]] #Fitting nonlinear Regression Model Using Starting Values From Previous Part nonlinearmod2 <- nls(mymod2, start = list(theta1 = trysol2$coefficients[[1]], theta2 = trysol2$coefficients[[2]], theta3 = trysol2$coefficients[[3]]), data = mod14data2_random) And I got this error: Error in nlsModel(formula, mf, start, wts, scaleOffset = scOff, nDcentral = nDcntr) : singular gradient matrix at initial parameter estimates Any idea on how to proceed in this situation? What could I do? Kind regards, Paul [[alternative HTML version deleted]] __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
Re: [R] Issues when trying to fit a nonlinear regression model
Oh, sorry; I changed signs in the model, fitting theta0 + theta1*exp(theta2*x) So for theta0 - theta1*exp(-theta2*x) use theta1= -.exp(-1.8) and theta2 = +.055 as starting values. -- Bert On Sun, Aug 20, 2023 at 11:50 AM Paul Bernal wrote: > Dear Bert, > > Thank you so much for your kind and valuable feedback. I tried finding the > starting values using the approach you mentioned, then did the following to > fit the nonlinear regression model: > nlregmod2 <- nls(y ~ theta1 - theta2*exp(-theta3*x), > start = > list(theta1 = 0.37, > theta2 = exp(-1.8), > theta3 = -0.05538), data=mod14data2_random) > However, I got this error: > Error in nls(y ~ theta1 - theta2 * exp(-theta3 * x), start = list(theta1 = > 0.37, : > step factor 0.000488281 reduced below 'minFactor' of 0.000976562 > nlregmod2 <- nlxb(y ~ theta1 - theta2*exp(-theta3*x), > start = > list(theta1 = 0.37, > theta2 = exp(-1.8), > theta3 = -0.05538), data=mod14data2_random) > summary(nlregmod2) > Object has try-error or missing parameters > nlregmod2 > And I get some NA values when retrieving the statistics for the fitted > model: > residual sumsquares = 0.0022973 on 15 observations > after 2235Jacobian and 2861 function evaluations > namecoeff SE tstat pval gradient > JSingval > theta1 9330.89NA NA NA 5.275e-11 >967470 > theta2 9330.41NA NA NA -5.318e-11 > 1.772 > theta3 -3.0032e-07NA NA NA 1.389e-05 > 8.028e-12 > > Kind regards, > Paul > > > El dom, 20 ago 2023 a las 13:21, Bert Gunter () > escribió: > >> I got starting values as follows: >> Noting that the minimum data value is .38, I fit the linear model log(y - >> .37) ~ x to get intercept = -1.8 and slope = -.055. So I used .37, >> exp(-1.8) and -.055 as the starting values for theta0, theta1, and theta2 >> in the nonlinear model. This converged without problems. >> >> Cheers, >> Bert >> >> >> On Sun, Aug 20, 2023 at 10:15 AM Paul Bernal >> wrote: >> >>> Dear friends, >>> >>> This is the dataset I am currently working with: >>> >dput(mod14data2_random) >>> structure(list(index = c(14L, 27L, 37L, 33L, 34L, 16L, 7L, 1L, >>> 39L, 36L, 40L, 19L, 28L, 38L, 32L), y = c(0.44, 0.4, 0.4, 0.4, >>> 0.4, 0.43, 0.46, 0.49, 0.41, 0.41, 0.38, 0.42, 0.41, 0.4, 0.4 >>> ), x = c(16, 24, 32, 30, 30, 16, 12, 8, 36, 32, 36, 20, 26, 34, >>> 28)), row.names = c(NA, -15L), class = "data.frame") >>> >>> I did the following to try to fit a nonlinear regression model: >>> >>> #First, Procedure to Find Starting (initial) Values For Theta1, Theta2, >>> and >>> Theta3 >>> >>> mymod2 <- y ~ theta1 - theta2*exp(-theta3*x) >>> >>> strt2 <- c(theta1 = 1, theta2 = 2, theta3 = 3) >>> >>> trysol2<-nlxb(formula=mymod2, data=mod14data2_random, start=strt2, >>> trace=TRUE) >>> trysol2 >>> trysol2$coefficients[[3]] >>> >>> #Fitting nonlinear Regression Model Using Starting Values From Previous >>> Part >>> nonlinearmod2 <- nls(mymod2, start = list(theta1 = >>> trysol2$coefficients[[1]], >>> theta2 = trysol2$coefficients[[2]], >>> theta3 = trysol2$coefficients[[3]]), data = >>> mod14data2_random) >>> >>> And I got this error: >>> Error in nlsModel(formula, mf, start, wts, scaleOffset = scOff, >>> nDcentral = >>> nDcntr) : >>> singular gradient matrix at initial parameter estimates >>> >>> Any idea on how to proceed in this situation? What could I do? >>> >>> Kind regards, >>> Paul >>> >>> [[alternative HTML version deleted]] >>> >>> __ >>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >>> https://stat.ethz.ch/mailman/listinfo/r-help >>> PLEASE do read the posting guide >>> http://www.R-project.org/posting-guide.html >>> and provide commented, minimal, self-contained, reproducible code. >>> >> [[alternative HTML version deleted]] __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Issues when trying to fit a nonlinear regression model
I haven't looked to see whether you or Bert made an algebraic mistake in translating the parameters of the log-linear model to their equivalents for the nonlinear model, but nls() gives me the same answer as nls() in this case (I called my data 'dd2'): n1 <- nlxb(y~theta1 - theta2*exp(-theta3*(x-8)), start = list(theta1 = 0.4, theta2 = -0.1, theta3 = 1/5), data = dd2) cc <- coef(n1) start2 <- with(as.list(cc), list(theta1 = theta1, theta2 = theta2*exp(theta3*8), theta3 = theta3)) unlist(start2) n2 <- nlxb(y~theta1 - theta2*exp(-theta3*x), start = start2, data = dd2) all.equal(unlist(start2), c(coef(n2)), tolerance = 1e-7) cc2 <- coef(n2) nlregmod2 <- nls(y ~ theta1 - theta2*exp(-theta3*x), start = list(theta1 = cc2[["theta1"]], theta2 = cc2[["theta2"]], theta3 = cc2[["theta3"]]), data=dd2) On 2023-08-20 2:50 p.m., Paul Bernal wrote: Dear Bert, Thank you so much for your kind and valuable feedback. I tried finding the starting values using the approach you mentioned, then did the following to fit the nonlinear regression model: nlregmod2 <- nls(y ~ theta1 - theta2*exp(-theta3*x), start = list(theta1 = 0.37, theta2 = exp(-1.8), theta3 = -0.05538), data=mod14data2_random) However, I got this error: Error in nls(y ~ theta1 - theta2 * exp(-theta3 * x), start = list(theta1 = 0.37, : step factor 0.000488281 reduced below 'minFactor' of 0.000976562 nlregmod2 <- nlxb(y ~ theta1 - theta2*exp(-theta3*x), start = list(theta1 = 0.37, theta2 = exp(-1.8), theta3 = -0.05538), data=mod14data2_random) summary(nlregmod2) Object has try-error or missing parameters nlregmod2 And I get some NA values when retrieving the statistics for the fitted model: residual sumsquares = 0.0022973 on 15 observations after 2235Jacobian and 2861 function evaluations namecoeff SE tstat pval gradient JSingval theta1 9330.89NA NA NA 5.275e-11 967470 theta2 9330.41NA NA NA -5.318e-11 1.772 theta3 -3.0032e-07NA NA NA 1.389e-05 8.028e-12 Kind regards, Paul El dom, 20 ago 2023 a las 13:21, Bert Gunter () escribió: I got starting values as follows: Noting that the minimum data value is .38, I fit the linear model log(y - .37) ~ x to get intercept = -1.8 and slope = -.055. So I used .37, exp(-1.8) and -.055 as the starting values for theta0, theta1, and theta2 in the nonlinear model. This converged without problems. Cheers, Bert On Sun, Aug 20, 2023 at 10:15 AM Paul Bernal wrote: Dear friends, This is the dataset I am currently working with: dput(mod14data2_random) structure(list(index = c(14L, 27L, 37L, 33L, 34L, 16L, 7L, 1L, 39L, 36L, 40L, 19L, 28L, 38L, 32L), y = c(0.44, 0.4, 0.4, 0.4, 0.4, 0.43, 0.46, 0.49, 0.41, 0.41, 0.38, 0.42, 0.41, 0.4, 0.4 ), x = c(16, 24, 32, 30, 30, 16, 12, 8, 36, 32, 36, 20, 26, 34, 28)), row.names = c(NA, -15L), class = "data.frame") I did the following to try to fit a nonlinear regression model: #First, Procedure to Find Starting (initial) Values For Theta1, Theta2, and Theta3 mymod2 <- y ~ theta1 - theta2*exp(-theta3*x) strt2 <- c(theta1 = 1, theta2 = 2, theta3 = 3) trysol2<-nlxb(formula=mymod2, data=mod14data2_random, start=strt2, trace=TRUE) trysol2 trysol2$coefficients[[3]] #Fitting nonlinear Regression Model Using Starting Values From Previous Part nonlinearmod2 <- nls(mymod2, start = list(theta1 = trysol2$coefficients[[1]], theta2 = trysol2$coefficients[[2]], theta3 = trysol2$coefficients[[3]]), data = mod14data2_random) And I got this error: Error in nlsModel(formula, mf, start, wts, scaleOffset = scOff, nDcentral = nDcntr) : singular gradient matrix at initial parameter estimates Any idea on how to proceed in this situation? What could I do? Kind regards, Paul [[alternative HTML version deleted]] __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. [[alternative HTML version deleted]] __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __
Re: [R] Issues when trying to fit a nonlinear regression model
Dear Bert, Thank you so much for your kind and valuable feedback. I tried finding the starting values using the approach you mentioned, then did the following to fit the nonlinear regression model: nlregmod2 <- nls(y ~ theta1 - theta2*exp(-theta3*x), start = list(theta1 = 0.37, theta2 = exp(-1.8), theta3 = -0.05538), data=mod14data2_random) However, I got this error: Error in nls(y ~ theta1 - theta2 * exp(-theta3 * x), start = list(theta1 = 0.37, : step factor 0.000488281 reduced below 'minFactor' of 0.000976562 nlregmod2 <- nlxb(y ~ theta1 - theta2*exp(-theta3*x), start = list(theta1 = 0.37, theta2 = exp(-1.8), theta3 = -0.05538), data=mod14data2_random) summary(nlregmod2) Object has try-error or missing parameters nlregmod2 And I get some NA values when retrieving the statistics for the fitted model: residual sumsquares = 0.0022973 on 15 observations after 2235Jacobian and 2861 function evaluations namecoeff SE tstat pval gradient JSingval theta1 9330.89NA NA NA 5.275e-11 967470 theta2 9330.41NA NA NA -5.318e-11 1.772 theta3 -3.0032e-07NA NA NA 1.389e-05 8.028e-12 Kind regards, Paul El dom, 20 ago 2023 a las 13:21, Bert Gunter () escribió: > I got starting values as follows: > Noting that the minimum data value is .38, I fit the linear model log(y - > .37) ~ x to get intercept = -1.8 and slope = -.055. So I used .37, > exp(-1.8) and -.055 as the starting values for theta0, theta1, and theta2 > in the nonlinear model. This converged without problems. > > Cheers, > Bert > > > On Sun, Aug 20, 2023 at 10:15 AM Paul Bernal > wrote: > >> Dear friends, >> >> This is the dataset I am currently working with: >> >dput(mod14data2_random) >> structure(list(index = c(14L, 27L, 37L, 33L, 34L, 16L, 7L, 1L, >> 39L, 36L, 40L, 19L, 28L, 38L, 32L), y = c(0.44, 0.4, 0.4, 0.4, >> 0.4, 0.43, 0.46, 0.49, 0.41, 0.41, 0.38, 0.42, 0.41, 0.4, 0.4 >> ), x = c(16, 24, 32, 30, 30, 16, 12, 8, 36, 32, 36, 20, 26, 34, >> 28)), row.names = c(NA, -15L), class = "data.frame") >> >> I did the following to try to fit a nonlinear regression model: >> >> #First, Procedure to Find Starting (initial) Values For Theta1, Theta2, >> and >> Theta3 >> >> mymod2 <- y ~ theta1 - theta2*exp(-theta3*x) >> >> strt2 <- c(theta1 = 1, theta2 = 2, theta3 = 3) >> >> trysol2<-nlxb(formula=mymod2, data=mod14data2_random, start=strt2, >> trace=TRUE) >> trysol2 >> trysol2$coefficients[[3]] >> >> #Fitting nonlinear Regression Model Using Starting Values From Previous >> Part >> nonlinearmod2 <- nls(mymod2, start = list(theta1 = >> trysol2$coefficients[[1]], >> theta2 = trysol2$coefficients[[2]], >> theta3 = trysol2$coefficients[[3]]), data = >> mod14data2_random) >> >> And I got this error: >> Error in nlsModel(formula, mf, start, wts, scaleOffset = scOff, nDcentral >> = >> nDcntr) : >> singular gradient matrix at initial parameter estimates >> >> Any idea on how to proceed in this situation? What could I do? >> >> Kind regards, >> Paul >> >> [[alternative HTML version deleted]] >> >> __ >> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> > [[alternative HTML version deleted]] __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Issues when trying to fit a nonlinear regression model
My answer is WAY longer than Bert Gunter's but maybe useful nonetheless. (Q for John Nash: why does the coef() method for nlmrt objects return the coefficient vector **invisibly**? That seems confusing!) Here's what I did: * as a preliminary step, adjust the formula so that I don't have to think as hard to eyeball starting values from the plot: in particular, replace (x) with (x-8) so that the data start from x = 0 * with this adjustment, we can approximate as follows: * theta1-theta2 is the value at (x' = 0) (or x = 8) * theta1 is the value as x goes to infinity * so since y(0) approx. 0.5 and y(inf) approx 0.4, we can use theta1 = 0.4, theta2 = -0.1 * theta3 gives the rate of decline. Since the curve drops by *approximately* a factor of e over the range from x'=0 to x'=5, 1/5 should be a good starting value for this n1 <- nlxb(y~theta1 - theta2*exp(-theta3*(x-8)), start = list(theta1 = 0.4, theta2 = -0.1, theta3 = 1/5), data = dd2) residual sumsquares = 0.00076151 on 15 observations after 6Jacobian and 9 function evaluations namecoeff SE tstat pval gradient JSingval theta1 0.391967 0.006128 63.96 0 -2.629e-11 4.085 theta2-0.0997234 0.007897 -12.63 2.733e-08 -1.035e-12 0.9956 theta3 0.107376 0.02365 4.54 0.0006777 -1.327e-11 0.3276 Now if the formula is theta1 - theta2*exp(-theta3*(x-8)) this is equivalent to theta1 - theta2*exp(-theta3*x)*exp(8*theta3) = theta1 - (theta2*exp(8*theta3))*exp(-theta3*x)) cc <- coef(n1) start2 <- with(as.list(cc), list(theta1 = theta1, theta2 = theta2*exp(8*theta3), theta3 = theta3)) unlist(start2) theta1 theta2 theta3 0.39197 -0.23543 0.10738 To confirm, rerun the fit with these starting values: n1 <- nlxb(y~theta1 - theta2*exp(-theta3*x), start = start2, data = dd2) nlmrt class object: x residual sumsquares = 0.00076151 on 15 observations after 4Jacobian and 5 function evaluations namecoeff SE tstat pval gradient JSingval theta1 0.391967 0.006128 63.96 0 -4.066e-12 4.228 theta2 -0.235429 0.04553 -5.171 0.0002328 3.151e-12 0.8508 theta3 0.107376 0.02365 4.54 0.0006777 -5.795e-12 0.1569 On 2023-08-20 1:15 p.m., Paul Bernal wrote: Dear friends, This is the dataset I am currently working with: dput(mod14data2_random) structure(list(index = c(14L, 27L, 37L, 33L, 34L, 16L, 7L, 1L, 39L, 36L, 40L, 19L, 28L, 38L, 32L), y = c(0.44, 0.4, 0.4, 0.4, 0.4, 0.43, 0.46, 0.49, 0.41, 0.41, 0.38, 0.42, 0.41, 0.4, 0.4 ), x = c(16, 24, 32, 30, 30, 16, 12, 8, 36, 32, 36, 20, 26, 34, 28)), row.names = c(NA, -15L), class = "data.frame") I did the following to try to fit a nonlinear regression model: #First, Procedure to Find Starting (initial) Values For Theta1, Theta2, and Theta3 mymod2 <- y ~ theta1 - theta2*exp(-theta3*x) strt2 <- c(theta1 = 1, theta2 = 2, theta3 = 3) trysol2<-nlxb(formula=mymod2, data=mod14data2_random, start=strt2, trace=TRUE) trysol2 trysol2$coefficients[[3]] #Fitting nonlinear Regression Model Using Starting Values From Previous Part nonlinearmod2 <- nls(mymod2, start = list(theta1 = trysol2$coefficients[[1]], theta2 = trysol2$coefficients[[2]], theta3 = trysol2$coefficients[[3]]), data = mod14data2_random) And I got this error: Error in nlsModel(formula, mf, start, wts, scaleOffset = scOff, nDcentral = nDcntr) : singular gradient matrix at initial parameter estimates Any idea on how to proceed in this situation? What could I do? Kind regards, Paul [[alternative HTML version deleted]] __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Issues when trying to fit a nonlinear regression model
I got starting values as follows: Noting that the minimum data value is .38, I fit the linear model log(y - .37) ~ x to get intercept = -1.8 and slope = -.055. So I used .37, exp(-1.8) and -.055 as the starting values for theta0, theta1, and theta2 in the nonlinear model. This converged without problems. Cheers, Bert On Sun, Aug 20, 2023 at 10:15 AM Paul Bernal wrote: > Dear friends, > > This is the dataset I am currently working with: > >dput(mod14data2_random) > structure(list(index = c(14L, 27L, 37L, 33L, 34L, 16L, 7L, 1L, > 39L, 36L, 40L, 19L, 28L, 38L, 32L), y = c(0.44, 0.4, 0.4, 0.4, > 0.4, 0.43, 0.46, 0.49, 0.41, 0.41, 0.38, 0.42, 0.41, 0.4, 0.4 > ), x = c(16, 24, 32, 30, 30, 16, 12, 8, 36, 32, 36, 20, 26, 34, > 28)), row.names = c(NA, -15L), class = "data.frame") > > I did the following to try to fit a nonlinear regression model: > > #First, Procedure to Find Starting (initial) Values For Theta1, Theta2, and > Theta3 > > mymod2 <- y ~ theta1 - theta2*exp(-theta3*x) > > strt2 <- c(theta1 = 1, theta2 = 2, theta3 = 3) > > trysol2<-nlxb(formula=mymod2, data=mod14data2_random, start=strt2, > trace=TRUE) > trysol2 > trysol2$coefficients[[3]] > > #Fitting nonlinear Regression Model Using Starting Values From Previous > Part > nonlinearmod2 <- nls(mymod2, start = list(theta1 = > trysol2$coefficients[[1]], > theta2 = trysol2$coefficients[[2]], > theta3 = trysol2$coefficients[[3]]), data = > mod14data2_random) > > And I got this error: > Error in nlsModel(formula, mf, start, wts, scaleOffset = scOff, nDcentral = > nDcntr) : > singular gradient matrix at initial parameter estimates > > Any idea on how to proceed in this situation? What could I do? > > Kind regards, > Paul > > [[alternative HTML version deleted]] > > __ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > [[alternative HTML version deleted]] __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Issues when trying to fit a nonlinear regression model
Dear friends, This is the dataset I am currently working with: >dput(mod14data2_random) structure(list(index = c(14L, 27L, 37L, 33L, 34L, 16L, 7L, 1L, 39L, 36L, 40L, 19L, 28L, 38L, 32L), y = c(0.44, 0.4, 0.4, 0.4, 0.4, 0.43, 0.46, 0.49, 0.41, 0.41, 0.38, 0.42, 0.41, 0.4, 0.4 ), x = c(16, 24, 32, 30, 30, 16, 12, 8, 36, 32, 36, 20, 26, 34, 28)), row.names = c(NA, -15L), class = "data.frame") I did the following to try to fit a nonlinear regression model: #First, Procedure to Find Starting (initial) Values For Theta1, Theta2, and Theta3 mymod2 <- y ~ theta1 - theta2*exp(-theta3*x) strt2 <- c(theta1 = 1, theta2 = 2, theta3 = 3) trysol2<-nlxb(formula=mymod2, data=mod14data2_random, start=strt2, trace=TRUE) trysol2 trysol2$coefficients[[3]] #Fitting nonlinear Regression Model Using Starting Values From Previous Part nonlinearmod2 <- nls(mymod2, start = list(theta1 = trysol2$coefficients[[1]], theta2 = trysol2$coefficients[[2]], theta3 = trysol2$coefficients[[3]]), data = mod14data2_random) And I got this error: Error in nlsModel(formula, mf, start, wts, scaleOffset = scOff, nDcentral = nDcntr) : singular gradient matrix at initial parameter estimates Any idea on how to proceed in this situation? What could I do? Kind regards, Paul [[alternative HTML version deleted]] __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
