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Selected Publications
Moffa, G., Kuipers, J., Kuipers, E., McManus, S., & Bebbington, P. (2023). Sexual abuse and psychotic phenomena: A directed acyclic graph analysis of affective symptoms using English national psychiatric survey data. Psychological Medicine, 53(16), 7817–7826. https://doi.org/10.1017/S003329172300185X
Moffa, G., Kuipers, J., Kuipers, E., McManus, S., & Bebbington, P. (2023). Sexual abuse and psychotic phenomena: A directed acyclic graph analysis of affective symptoms using English national psychiatric survey data. Psychological Medicine, 53(16), 7817–7826. https://doi.org/10.1017/S003329172300185X
Giudice, E., Kuipers, J., & Moffa, G. (2023). The dual PC algorithm and the role of Gaussianity for structure learning of Bayesian networks. International Journal of Approximate Reasoning, 161. https://doi.org/10.1016/j.ijar.2023.108975
Giudice, E., Kuipers, J., & Moffa, G. (2023). The dual PC algorithm and the role of Gaussianity for structure learning of Bayesian networks. International Journal of Approximate Reasoning, 161. https://doi.org/10.1016/j.ijar.2023.108975
, Kuipers Jack, Carrà Giuseppe, Crocamo Cristina, Kuipers Elizabeth, Angermeyer Matthias, Brugha Traolach, Toumi Mondher, & Bebbington Paul. (2023). Longitudinal symptomatic interactions in long-standing schizophrenia: A novel five-point analysis based on directed acyclic graphs. Psychological Medicine, 53(4), 1371–1378. https://doi.org/10.1017/S0033291721002920
, Kuipers Jack, Carrà Giuseppe, Crocamo Cristina, Kuipers Elizabeth, Angermeyer Matthias, Brugha Traolach, Toumi Mondher, & Bebbington Paul. (2023). Longitudinal symptomatic interactions in long-standing schizophrenia: A novel five-point analysis based on directed acyclic graphs. Psychological Medicine, 53(4), 1371–1378. https://doi.org/10.1017/S0033291721002920
Luo, Xiang Ge, , & Kuipers, Jack. (2021). Learning Bayesian networks from ordinal data. Journal of Machine Learning Research, 22.
Luo, Xiang Ge, , & Kuipers, Jack. (2021). Learning Bayesian networks from ordinal data. Journal of Machine Learning Research, 22.
Kuipers, Jack, & . (2017). Partition MCMC for Inference on Acyclic Digraphs. Journal of the American Statistical Association, 112(417), 282–299. https://doi.org/10.1080/01621459.2015.1133426
Kuipers, Jack, & . (2017). Partition MCMC for Inference on Acyclic Digraphs. Journal of the American Statistical Association, 112(417), 282–299. https://doi.org/10.1080/01621459.2015.1133426