para_data: Simulated parasite abundance data for multiple species across...

In parasiteR: A Theorical-Practical Approach to Parasitological Data Analysis

Simulated parasite abundance data for multiple species across hosts and sites

Description

This dataset contains hypothetical generated parasite count data representing multiple parasite species infecting individual hosts across different sampling sites. Each row corresponds to a single sampling unit (i.e., an individual host), and parasite abundance is recorded as counts for each parasite species (Sp1–Sp4).

Usage

para_data

Format

## 'para_data' A list with 4 elements

• dataset A data frame with 81 rows and 6 columns:

  • Site: Factor or character. Sampling location where hosts were collected (sites A, B, C and D). Multiple hosts can belong to the same site.

  • Factor or character. Host species identifier. In this dataset, each site includes up to two host species (HostA, HostB), although some site–host combinations may be absent by design.

  • Sp1: Integer. Abundance (count) of parasite species 1 per host. Simulated using an aggregated (negative binomial) distribution across all sites.

  • Sp2: Integer. Abundance of parasite species 2 per host. Present only in Sites A and B; missing (NA) in Site C to represent non-analyzed combinations.

  • Sp3: Integer. Abundance of parasite species 3 per host. Designed to represent heterogeneous infection patterns: full infection in one host group, rare infection in another and absence elsewhere.

  • Sp4: Integer. Integer. Abundance of parasite species 4 per host. Includes several edge cases:only one host examined, no infected hosts, a single infected host, multiple infected hosts.

• factors_v: A list of columns with factor values.

• num_v: A list of columns with numeric values.

• summ: A summary of the loaded data. Check summary.

Details

The dataset was intentionally constructed to reproduce common scenarios encountered in parasitological studies, rather than to reflect a specific empirical system. These scenarios include:

• zero-inflated parasite distributions

• aggregated parasite abundances

• missing data (non-analyzed host–parasite combinations)

• rare infections (single infected host)

• absence of infection

• small sample sizes for specific host–site combinations

This structure allows testing and demonstrating the behavior of analytical functions under realistic and edge-case conditions.

parasiteR documentation built on May 13, 2026, 9:08 a.m.