model {
// likelihood of diagnostic infection intensities
for (j in 1:n_x) {
target += lognormal_lupdf(x[j] | log_n[ind[j]][sec[j], prim[j]], sigma[3]);
}
// likelihood of multievent model (threading)
target += reduce_sum(partial_sum_lupmf, seq_ind, grainsize, y, q,
n_prim, n_sec, first, last, first_sec, tau, temp,
phi_a, phi_b, psi_a, psi_b, p_a, r, lambda, m, n_z, sigma);
}What We Do
Quantecol offers a range of methodological and analytical services for efficient, effective, and honest scientific inference.
Study Design and Methodology
Data forms the foundation of scientific studies but not all data are created equal. Statistical models make non-trivial assumptions about how the data were collected which influence the validity of your conclusions. We can provide you with study designs tailored to your system, with recommendations for appropriate sample sizes, surveying schemes, and more.
Data Analysis
Your datasets often contain a wealth of information but complex models are frequently required to reveal these signals. We can help you with this process, ranging from tutorials and workshops for applying statistical methodology, to conducting the entire analysis for you in a clear, collaborative fashion.
Visualisation and Reporting
Communication of key results derived from our data is what advances scientific fields. We believe that honest reporting involves an appropriate display of uncertainty and does not hide the raw data. The services we offer are predicated on transparency and scientific integrity.
