It does that with analytical solutions for linear trends and Monte Carlo simulations
for nonlinear trends.
Not exact matches
Everyone should consider the possibility that
for some indices, North Atlantic correlations (in correlation maps) are depressed by the North Atlantic's sensitivity (being the smaller northern basin surrounded by a lot of land / ice, resulting «higher continentality»), which gives it a propensity towards high amplitude oscillations, including decadal - timescale
nonlinear trends.
I hate idiots that compute linear
trends for nonlinear phenomenon.
A generalized
nonlinear mixed model was used
for modeling temporal
trends of tree mortality and recruitment rates, and a linear mixed model was used
for modeling temporal
trends of tree growth rates (Methods).
Different approaches have been used to compute the mean rate of 20th century global mean sea level (GMSL) rise from the available tide gauge data: computing average rates from only very long, nearly continuous records; using more numerous but shorter records and filters to separate
nonlinear trends from decadal - scale quasi-periodic variability; neural network methods; computing regional sea level
for specific basins then averaging; or projecting tide gauge records onto empirical orthogonal functions (EOFs) computed from modern altimetry or EOFs from ocean models.