Overview
Origins and design
Graphical models
How to read a DAG?
Specifying a model (an example)
Multiple samples and replicates
Graphical user interface (GUI)
Implementation comparison
Coverage validation
Command-line interface (CLI)
Bypassing the interfaces
Lexicon
Parametric distributions
Uniform
Exponential
Gamma
Normal
Log-normal
Tree distributions
Discrete SSE
det_sampling_prob := sse_prob(name="rho", value=1.0, state=0) # by setting the value to 1.0, we assume complete sampling!
epoch
sse_rate
sse_prob
epoch_age_ends
det_birth_rate1 := sse_rate(name="lambda1", value=1.0, event="speciation") -det_birth_rate2 := sse_rate(name="lambda2", value=2.0, event="speciation") +Script excerpt 3. Command in the phylojunction language to organize rate and probability parameters into a stash (a deterministic node in the DAG). +det_birth_rate1 := sse_rate(name="lambda1", value=1.0, event="speciation", epoch=1) +det_birth_rate2 := sse_rate(name="lambda2", value=2.0, event="speciation", epoch=2) stash := sse_stash(flat_rate_mat=[det_birth_rate1, det_birth_rate2], n_epochs=2, seed_age=2.0, epoch_age_ends=[1.0]) # there are two epochs, the oldest one ends at age 1.0, the youngest one ends at the present @@ -658,6 +658,31 @@ Discrete SSEruntime_limit (positive integer, optional): Maximum number of minutes to wait until all samples are drawn. Sampling is aborted at this point. Defaults to 5.
det_birth_rate1 := sse_rate(name="lambda1", value=1.0, event="speciation", epoch=1) +det_birth_rate2 := sse_rate(name="lambda2", value=2.0, event="speciation", epoch=2) stash := sse_stash(flat_rate_mat=[det_birth_rate1, det_birth_rate2], n_epochs=2, seed_age=2.0, epoch_age_ends=[1.0]) # there are two epochs, the oldest one ends at age 1.0, the youngest one ends at the present @@ -658,6 +658,31 @@ Discrete SSEruntime_limit (positive integer, optional): Maximum number of minutes to wait until all samples are drawn. Sampling is aborted at this point. Defaults to 5.
runtime_limit
Below, an example of assigning a discrete SSE to a stochastic DAG node representing phylogenetic tree samples:
det_birth_rate1 := sse_rate(name="lambda1", value=1.0, event="speciation", epoch=1) +det_birth_rate2 := sse_rate(name="lambda2", value=2.0, event="speciation", epoch=2) + +stash := sse_stash(flat_rate_mat=[det_birth_rate1, det_birth_rate2], n_epochs=2, seed_age=2.0, epoch_age_ends=[1.0]) + +trs ~ discrete_sse(n=2, stash=stash, start_state=[0,0], stop="age", stop_value=2.0, origin="true") +
For examples of different models that can be simulated with discrete_sse, see:
discrete_sse
+ +Yule (pure-birth) model; +Birth-death model; +Birth-death with incomplete sampling model; +Fossilized birth-death (FBD) model; +Binary state-dependent speciation and extinction (BiSSE) model; +Time-heterogeneous binary state-dependent speciation and extinction (skyline BiSSE) model; +Geographic state-dependent speciation and extinction (GeoSSE) model; +Time-heterogeneous geographic state-dependent speciation and extinction (skyline GeoSSE) model; + +
Yule (pure-birth) model;
Birth-death model;
Birth-death with incomplete sampling model;
Fossilized birth-death (FBD) model;
Binary state-dependent speciation and extinction (BiSSE) model;
Time-heterogeneous binary state-dependent speciation and extinction (skyline BiSSE) model;
Geographic state-dependent speciation and extinction (GeoSSE) model;
Time-heterogeneous geographic state-dependent speciation and extinction (skyline GeoSSE) model;