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Longitudinal mixed models were also used to estimate the effect of vaccine dose on mean log-transformed antibody levels over time, using a spatial exponential covariance structure to model the correlation between measurements from the same individual while taking into account the number of study days between measurements.
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A spatial exponential covariance structure was used to model the correlation between measurements from the same individual taking into account the number of study days between each measurement.
A spatial exponential covariance structure was used to model the correlations between repeated measurements.
We assumed a spatial exponential covariance structure because the intervals between serial data points were different by design.
A model with fixed effects only gave the lowest AIC statistic, and a spatial exponential covariance structure had the best fit.
Here, the random effects arise from a spatial Gaussian process with a covariance matrix constructed using an exponential spatial correlation function.
The spatial sampling probabilities are computed by using a normalized exponential loss function.
Collisions are resolved using a random exponential backoff process.
Missing data were replaced using a simple exponential smoothing method.
The raw data were filtered in the spatial domain using a hamming-window and in the spectral domain using a matched exponential-filter.
Deactivation kinetics were well-fit using a single standard exponential.
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