# Calculate combined probabilities of similarity or intersection metrics of tracks `combined_prob()` calculates the combined probabilities of similarity and intersection metrics derived from different models. The function uses simulation data to extract **p**-values, providing insight into the significance of combined metrics across various similarity assessments. ```r combined_prob(data, metrics = NULL) ``` ## Arguments - `data`: A `track` R object, which is a list consisting of two elements: * ‘Trajectories’ : A list of interpolated trajectories, where each trajectory is a series of midpoints between consecutive footprints. * ‘Footprints’ : A list of data frames containing footprint coordinates, metadata (e.g., image reference, ID), and a marker indicating whether the footprint is actual or inferred. - `metrics`: A list of `track similarity` and/or `track intersection` R objects derived from different tests. All tests must be based on the same number of simulations. ## Returns A list containing: - **P_values (model names)**: A matrix of **p**-values for the combined metrics across all trajectories. Each entry represents the probability of observing the combined metrics between the corresponding pair of trajectories. - **P_values_combined (model names)**: A numeric value representing the overall probability of observing the combined metrics, across all pairs of trajectories. ## Details The `combined_prob()` function combines **p**-values derived from multiple similarity metric tests and intersection tests. It calculates the combined **p**-values by assessing the probability of observing the combined metrics across simulated datasets. This function is particularly useful for comparing multiple models and evaluating their collective performance in terms of **p**-values. ## Logo ## Examples ```r # Example 1: "Directed" model and similarity metrics. s1 <- simulate_track(PaluxyRiver, nsim = 3, model = "Directed") DTW1 <- simil_DTW_metric(PaluxyRiver, test = TRUE, sim = s1, superposition = "None") Frechet1 <- simil_Frechet_metric(PaluxyRiver, test = TRUE, sim = s1, superposition = "None") int1 <- track_intersection(PaluxyRiver, test = TRUE, H1 = "Lower", sim = s1, origin.permutation = "None") combined_prob(PaluxyRiver, metrics = list(DTW1, Frechet1, int1)) # Example 2: "Constrained" model and similarity metrics. s2 <- simulate_track(PaluxyRiver, nsim = 3, model = "Constrained") DTW2 <- simil_DTW_metric(PaluxyRiver, test = TRUE, sim = s2, superposition = "None") Frechet2 <- simil_Frechet_metric(PaluxyRiver, test = TRUE, sim = s2, superposition = "None") int2 <- track_intersection(PaluxyRiver, test = TRUE, H1 = "Lower", sim = s2, origin.permutation = "Min.Box") combined_prob(PaluxyRiver, metrics = list(DTW2, Frechet2, int2)) # Example 3: "Unconstrained" model and similarity metrics. s3 <- simulate_track(PaluxyRiver, nsim = 3, model = "Unconstrained") DTW3 <- simil_DTW_metric(PaluxyRiver, test = TRUE, sim = s3, superposition = "None") Frechet3 <- simil_Frechet_metric(PaluxyRiver, test = TRUE, sim = s3, superposition = "None") int3 <- track_intersection(PaluxyRiver, test = TRUE, H1 = "Lower", sim = s3, origin.permutation = "Conv.Hull") combined_prob(PaluxyRiver, metrics = list(DTW3, Frechet3, int3)) ``` ## See Also `tps_to_track`, `simulate_track`, `track_intersection`, `simil_DTW_metric`, `simil_Frechet_metric` ## Author(s) Humberto G. Ferrón humberto.ferron@uv.es Macroevolution and Functional Morphology Research Group (www.macrofun.es) Cavanilles Institute of Biodiversity and Evolutionary Biology Calle Catedrático José Beltrán Martínez, nº 2 46980 Paterna - Valencia - Spain Phone: +34 (9635) 44477

combined_prob function