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A new likelihood inequality for models with latent variables

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  • Olsen, Niels Lundtorp

Abstract

Likelihood-based approaches are central in statistics and its applications, yet often challenging since likelihoods can be intractable. Many methods such as the EM algorithm have been developed to alleviate this.

Suggested Citation

  • Olsen, Niels Lundtorp, 2024. "A new likelihood inequality for models with latent variables," Statistics & Probability Letters, Elsevier, vol. 206(C).
    • Handle: RePEc:eee:stapro:v:206:y:2024:i:c:s0167715223002225
    DOI: 10.1016/j.spl.2023.109998
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    References listed on IDEAS

    as
    1. Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392, April.
    2. Niels Lundtorp Olsen & Bo Markussen & Lars Lau Raket, 2018. "Simultaneous inference for misaligned multivariate functional data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(5), pages 1147-1176, November.
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