Evaluates the normal distribution density function for summary data reported as sample mean, sample SD, and sample N. Sample mean and sample SD should be on the *natural* scale. If you have log-scale sample mean and SD (i.e., the mean and SD of log-transformed observations),then use [dnorm_summary()] instead.
dlnorm_summary(mu, sigma, x_mean, x_sd, x_N, log = FALSE)A numeric scalar or vector matching the length of the longest of `mu`, `sigma`, `x_mean`, `x_sd`, and `x_N`.
*Log-scale* mean of the log-normal distribution to be evaluated (*not* the sample mean). May be a numeric scalar or vector.
*Log-scale* standard deviation of the log-normal distribution to be evaluated (*not* the sample SD). May be a numeric scalar or vector.
Sample mean (on the *natural* scale). May be a numeric scalar or vector.
Sample standard deviation (on the *natural* scale). May be a numeric scalar or vector.
Sample number of observations. May be a numeric scalar or vector.
TRUE/FALSE: Whether to return the log of the density function (i.e., the log-likelihood). Default FALSE.
Caroline Ring
`x_mean`, `x_sd`, `X_N`, `mu`, and `sigma` should either be all the same size, or length 1. If they are different lengths, they will be repeated until their lengths match, with a warning.