Sentence examples for simple prior from inspiring English sources

Population structure was investigated using fastStructure with a simple prior (Raj et al. 2014) and visualized in distruct (Rosenberg 2004).

A simple prior sensitivity analysis suggests that our British and Danish mortality forecasts are relatively insensitive to the (rather weakly informative) prior specifications.

Given p(g|f) and any simple prior law p(f), the posterior law is written: p ( f g ) ∝ p ( g f ) p ( f ) ∝ exp { J ( f ) } (43).

For simple prior models: Simple optimization of p(f|θ, g) for the MAP: Joint optimization p f, θ|g) for joint MAP: Generation of samples from the conditionals p(f|θ, g) and p(θ|f, g) for the MCMC Gibbs sampling methods, Variational approximation (VA) of the joint p f, θ|g) by a separable q ( f, θ g ) = q 1 ( f θ ̃, g ) q 2 ( θ f ̃, g ) and then using them for estimation.

In CAVIAR, we use a simple prior for a causal SNP status.

It is worth mentioning that although we use a simple prior for our model, CAVIAR can incorporate external information such as functional data or knowledge from previous studies.

This endeavour allowed us to build a model using simple priors over the dynamics of the hidden causes that reproduces the sorts of anticipatory behaviour seen empirically.

He also introduced the Tunny team to Tommy Flowers who, under the guidance of Max Newman, went on to build the Colossus computer, the world's first programmable digital electronic computer, which replaced a simpler prior machine (the Heath Robinson), and whose superior speed allowed the statistical decryption techniques to be applied usefully to the messages.

Our model was, on one hand based on the simplest prior epidemic models (percolation), on the other hand it took into account some of the specifics of the present experiment in a new way.

ABSOLUTE incorporates prior probabilities from previous karyotype analyses, whereas Sequenza uses much simpler prior probabilities on copy numbers that are the same on each segment to estimate the best solution.

The intrinsic model (Besag et al., 1991; IAR) is the simplest prior in the CAR class, and its full conditional distributions are given by (2) The conditional expectation is the mean of the random effects in neighboring areas, while the conditional variance is inversely proportional to the number of neighbors.