search for: maxima_index

...: >> >> values <- rnorm(20, mean = c(2.15,2.0,2.9), sd = c(0.1,0.1,0.1)) >> >> v_dens <- density(values) >> v_dens_y <- v_dens$y >> >> r <- rle(v_dens_y) >> # These functions ignore the extremes if they are the first or last point >> maxima_index <- which(rep(x = diff(sign(diff(c(-Inf, r$values, -Inf)))) >> == -2, times = r$lengths)) >> minima_index <- which(rep(x = diff(sign(diff(c(-Inf, r$values, -Inf)))) >> == 2, times = r$lengths)) >> >> plot(v_dens_y) >> >> HTH >> Ulrik >> &...

I have a Gaussian mixture model with some parameters mean=(506.8644,672.8448,829.902) sigma=(61.02859,9.149168,74.84682) c=(0.1241933, 0.6329082, 0.2428986) And the plot look something like below.[image: enter image description here] <https://i.stack.imgur.com/4uUQ9.png> Also, if I change my parameters to mean=(2.15,2.0,2.9) sigma=(0.1,0.1,0.1) c=(1/3,1/3,1/3) Then plot would change

...d = c(0.1,0.1,0.1)) > >>> > >>> v_dens <- density(values) > >>> v_dens_y <- v_dens$y > >>> > >>> r <- rle(v_dens_y) > >>> # These functions ignore the extremes if they are the first or last > point > >>> maxima_index <- which(rep(x = diff(sign(diff(c(-Inf, r$values, > -Inf)))) > >>> == -2, times = r$lengths)) > >>> minima_index <- which(rep(x = diff(sign(diff(c(-Inf, r$values, > -Inf)))) > >>> == 2, times = r$lengths)) > >>> > >>> plot(v_...