1. In statistical models with latent variables , this is usually impossible. 2. Illumination variations can be explained by changing only the lighting latent variable . 3. The structural model represents the relationships between the latent variables . 4. Such a system is then called an observable ( latent variable ) system. 5. Factor analysis aims to find independent latent variables . 6. One advantage of using latent variables is that it reduces the dimensionality of data. 7. The measurement model represents the relationships between the observed data and the latent variables . 8. Unsupervised learning methods are often used to learn the parameters of latent variable models. 9. Therefore there may be a psychometrical latent variable , but not a psychological psychometric variable. 10. For every pixel i there are two latent variables namely the albedo and surface normal. 
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