Hi: Using nls how can I increase the numbers of iterations to go beyond 50. I just want to be able to predict for the last two weeks of the year. This is what I have:
weight_random <- runif(50,1,24) weight <- sort(weight_random);weight weightData <- data.frame(weight,week=1:50) weightData plot(weight ~ week, weightData) M_model <- nls(weight ~ alpha + beta*exp(gamma*week), weightData, start = c(alpha = 0.0, beta = 1, gamma = 0.2), trace = TRUE) ### I get the error below: Error in nls(weight ~ alpha + beta * exp(gamma * week), weightData, start = c(alpha = 0, : number of iterations exceeded maximum of 50 M_model ### predict for another 2 weeks newD <- data.frame(week = 1:52);newD newD$pred_wt <- predict(M_model, newD) newD plot(pred_wt ~ week, newD, pch = 4, col = "red", ylab = "Weight", xlab = "Week") with(weightData, points(week, weight,col='blue')) Felipe D. Carrillo Supervisory Fishery Biologist Department of the Interior US Fish & Wildlife Service California, USA http://www.fws.gov/redbluff/rbdd_jsmp.aspx [[alternative HTML version deleted]]
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