self start for non-rectangular hyperbola (photosynthesis)
Self starter for Non-rectangular Hyperbola with parameters: asymptote, quantum efficiency, curvature and dark respiration
nrh(x, asym, phi, theta, rd) SSnrh(x, asym, phi, theta, rd)
x |
input vector (x) which is normally light intensity (PPFD, Photosynthetic Photon Flux Density). |
asym |
asymptotic value for photosynthesis |
phi |
quantum efficiency (mol CO2 per mol of photons) or initial slope of the light response |
theta |
curvature parameter for smooth transition between limitations |
rd |
dark respiration or value of CO2 uptake at zero light levels |
This function is described in Archontoulis and Miguez (2015) - (doi:10.2134/agronj2012.0506).
a numeric vector of the same length as x (time) containing parameter estimates for equation specified
nrh: vector of the same length as x (time) using the non-rectangular hyperbola
require(ggplot2) set.seed(1234) x <- seq(0, 2000, 100) y <- nrh(x, 35, 0.04, 0.83, 2) + rnorm(length(x), 0, 0.5) dat <- data.frame(x = x, y = y) fit <- nls(y ~ SSnrh(x, asym, phi, theta, rd), data = dat) ## Visualize observed and simulated ggplot(data = dat, aes(x = x, y = y)) + geom_point() + geom_line(aes(y = fitted(fit))) ## Testing predict function prd <- predict_nls(fit, interval = "confidence") datA <- cbind(dat, prd) ## Plotting ggplot(data = datA, aes(x = x, y = y)) + geom_point() + geom_line(aes(y = fitted(fit))) + geom_ribbon(aes(ymin = Q2.5, ymax = Q97.5), fill = "purple", alpha = 0.3) x <- seq(0, 2000) y <- nrh(x, 30, 0.04, 0.85, 2) plot(x, y)
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