Quantitatively analyse depth time-series data from pop-up satellite archival tags (PSATs) through the application of continuous wavelet transformation (CWT) combined with Principal Component Analysis (PCA), and k-means clustering.
  Import, crop, and plot depth time-depth records (TDRs). Using CWT to detect important signals within the non-stationary data, we create daily wavelet statistics to summarise vertical movements on different wavelet periods and combine with daily and diel depth statistics.
  Classify depth time-series with unsupervised k-means clustering into 24-hour periods of vertical movement behaviour with distinct patterns of vertical movement. Plot example days from each behaviour cluster, and plot the TDR coloured by cluster.
  Based on principals of combining CWT with k-means first developed by Sakamoto (2009) <doi:10.1371/journal.pone.0005379> and redeveloped by Beale (2026) <doi:10.21203/rs.3.rs-6907076/v1>.

The FisherEM algorithm, proposed by Bouveyron & Brunet (2012) <doi:10.1007/s11222-011-9249-9>,
        is an efficient method for the clustering of high-dimensional data. FisherEM models and 
        clusters the data in a discriminative and low-dimensional latent subspace. It also provides
        a low-dimensional representation of the clustered data. A sparse version of Fisher-EM
        algorithm is also provided.

Base maps are transformed to focus on a specific location using an
    azimuthal logarithmic distance transformation.

Fit growth models to otoliths and/or tagging data, using the 'RTMB'
  package and maximum likelihood. The otoliths (or similar measurements of age)
  provide direct observed coordinates of age and length. The tagging data
  provide information about the observed length at release and length at
  recapture at a later time, where the age at release is unknown and estimated
  as a vector of parameters. The growth models provided by this package can be
  fitted to otoliths only, tagging data only, or a combination of the two.
  Growth variability can be modelled as constant or increasing with length.