plot_influence_diagram {movementsync} | R Documentation |
Plot influence diagram from a GrangerTest object
Description
Arrows show causality (influencing) direction.
Usage
plot_influence_diagram(obj, splicing_df, two_arrows = TRUE, lev_sig = 0.05)
Arguments
obj |
GrangerTest object |
splicing_df |
Splicing data.frame object |
two_arrows |
plot influence arrows both ways? (Default is TRUE). |
lev_sig |
significance level |
Details
By default two_arrows
is TRUE and an influencing arrow is drawn for each
significant p-value. If two_arrows
is FALSE and one
of the p-values is signficant then -log10(p_value) difference is plotted i.e
Value
ggplot object
See Also
Other Granger Causality:
autoplot.GrangerTime()
,
get_granger_interactions()
,
granger_test()
,
map_to_granger_test()
,
ms_condgrangertest()
,
ms_grangertest1()
,
ms_grangertest2()
,
plot.GrangerInteraction()
Examples
r1 <- get_sample_recording()
fv_list <- get_filtered_views(r1, data_points = "Nose", n = 41, p = 3)
jv_sub <- get_joined_view(fv_list)
splicing_df <- splice_time(jv_sub, win_size = 3, step_size = 0.5)
sv <- get_spliced_view(jv_sub, splicing_df)
g <- granger_test(sv, "Nose_x_Central_Sitar", "Nose_x_Central_Tabla", lag = 3/25)
plot_influence_diagram(g, splicing_df)
plot_influence_diagram(g, splicing_df, two_arrows = TRUE)
d1 <- get_duration_annotation_data(r1)
plot_influence_diagram(g, splicing_df) +
autolayer(d1, expr = (Tier == "Influence S>T" | Tier == "Influence T>S") & Out <= 60,
fill_col = "Tier")
[Package movementsync version 0.1.4 Index]