makeFits_OLS

<p>A list of data frames, where each frame contains the data for one individual. Every
data frame should have two columns with names 'distance' and 'oxygen'.</p>

paths

<p>Performs the nonlinear least squares (NLS) regression method for the cosine
model, with the proposed initialization for all the parameters. It fits the NLS method
as required, and then computes different quantities for the birth seasonality estimates
corresponding to different individuals.</p>

We introduce improved methods for statistically assessing birth seasonality and intra-annual variation. The first method we propose is a new idea that uses a nonparametric clustering procedure to group individuals with similar time series data and estimate birth seasonality based on the clusters. One can use the function SCEM() to implement this method. The second method estimates input parameters for use with a previously-developed parametric approach (Tornero et al., 2013). The relevant code for this approach is makeFits_OLS(), while makeFits_initial() is the code to implement the same method but with given initial conditions for two parameters. The latter can be used to show the disadvantage of the existing approach. One can use the function makeFits() to generate parametric birth seasonality estimates using either initialization. Detailed description can be found here: Chazin Hannah, Soudeep Deb, Joshua Falk, and Arun Srinivasan. (2019) "New Statistical Approaches to Intra-Individual Isotopic Analysis and Modeling Birth Seasonality in Studies of Herd Animals." <doi:10.1111/arcm.12432>.

Kyung Serk Cho

SCEM

Splitting-Coalescence-Estimation Method

Hannah Chazin

Soudeep Deb

Joshua Falk

Arun Srinivasan

makeFits_OLS function

Prepare results for cosine model fit with proposed initialization. — makeFits_OLS

Prepare results for cosine model fit with proposed initialization.

makeFits_OLS: Prepare results for cosine model fit with proposed initialization.

Description

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Examples