format_output: Run the EM for several values of K
In PhylogeneticEM: Automatic Shift Detection using a Phylogenetic EM
format_output R Documentation
Run the EM for several values of K
Description
estimateEM_several_K.OUsr uses function estimateEM on the data,
for all values of K between 0 and K_max.
Usage
format_output(results_estim_EM, phylo, time = NA)
Arguments
results_estim_EM
output of function estimateEM
time
to run the function
Details
The EM is first launched for K=0, with alpha and gamma estimated. The
estimated values of alpha, gamma and beta_0 found by this first EM are then
used as initialization parameters for all the other runs of the EM for other
K.
The EMs are parallelized thanks to packages foreach and
doParallel.
WARNING : this code only work of OU with stationary root, on an ultrametric
tree.
Value
summary a data frame with K_max lines, and columns:
- alpha_estim the estimated selection strength
- gamma_estim the estimated root variance
- beta_0_estim the estimated value of root optimum
- EM_steps number of iterations needed before convergence
- DV_estim has the EM diverged ?
- CV_estim has the EM converged ?
- log_likelihood log likelihood of the data using the estimated parameters
- mahalanobis_distance_data_mean the Mahalanobis distance between the data
and the estimated means at the tips
- least_squares the Mahalanobis distance, renormalized by gamma^2:
mahalanobis_distance_data_mean * gamma_estim.
- mean_number_new_shifts the mean number of shifts that changed over the
iterations of the EM
- number_equivalent_solutions the number of equivalent solutions to
the solution found.
- K_try the number of shifts allowed.
- complexity the complexity for K_try
- time the CPU time needed.
params a list of inferred parameters
params_init a list of initial parameters
alpha_0 initial values of alpha
gamma_0 initial values of gamma
Zhat reconstructed node states
m_Y_estim reconstructed tip states
edge.quality for each edge, relative number of iterations in which they
were present.
PhylogeneticEM documentation built on Aug. 31, 2022, 9:16 a.m.
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| format_output | R Documentation |
Run the EM for several values of K
Description
estimateEM_several_K.OUsr uses function estimateEM on the data,
for all values of K between 0 and K_max.
Usage
format_output(results_estim_EM, phylo, time = NA)
Arguments
results_estim_EM |
output of function |
time |
to run the function |
Details
The EM is first launched for K=0, with alpha and gamma estimated. The
estimated values of alpha, gamma and beta_0 found by this first EM are then
used as initialization parameters for all the other runs of the EM for other
K.
The EMs are parallelized thanks to packages foreach and
doParallel.
WARNING : this code only work of OU with stationary root, on an ultrametric
tree.
Value
summary a data frame with K_max lines, and columns: - alpha_estim the estimated selection strength - gamma_estim the estimated root variance - beta_0_estim the estimated value of root optimum - EM_steps number of iterations needed before convergence - DV_estim has the EM diverged ? - CV_estim has the EM converged ? - log_likelihood log likelihood of the data using the estimated parameters - mahalanobis_distance_data_mean the Mahalanobis distance between the data and the estimated means at the tips - least_squares the Mahalanobis distance, renormalized by gamma^2: mahalanobis_distance_data_mean * gamma_estim. - mean_number_new_shifts the mean number of shifts that changed over the iterations of the EM - number_equivalent_solutions the number of equivalent solutions to the solution found. - K_try the number of shifts allowed. - complexity the complexity for K_try - time the CPU time needed.
params a list of inferred parameters
params_init a list of initial parameters
alpha_0 initial values of alpha
gamma_0 initial values of gamma
Zhat reconstructed node states
m_Y_estim reconstructed tip states
edge.quality for each edge, relative number of iterations in which they were present.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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