The Latent Factor Analysis via Dynamical Systems (LFADS) is a sequential autoencoder-based method designed with the purpose of inferring single-trial dynamics of neural activity. The major part of the ...
A recent and growing area of research applies latent factor models to study the development of children's skills. Some normalization is required in these models because the latent variables have no ...
Please see this paper for more details on the Mini-Hes algorithm. Step 1: Download the model and dataset. Step 2: Modify the dataset path inside the Constant.java ...
We estimate a model that summarizes the yield curve using latent factors (specifically, level, slope, and curvature) and also includes observable macroeconomic variables (specifically, real activity, ...
Structural equation models are used to evaluate structural relationships between measured and latent variables. Examples are confirmatory factor analysis, latent growth models and mediation models.
Therefore, the present study aimed to investigate whether there are more homogeneous classes of forensic patients based on DSM-IV-TR Axis I and II diagnoses and previously committed offenses, by means ...
The true burden of LTBI in Africa is not known. Early modelling studies estimate that over 33% of the world’s population is infected with latent tuberculosis. We propose conducting a systematic review ...
Results There were four latent classes: low-risk (30.2%), high-risk (15.0%), clinical-risk (42.6% ... Both low social contact and social disengagement were generated by confirmatory factor analysis ...