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Author: search.filters.author.Udomboso, C. G.Subject: search.filters.subject.Statistical neural network

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Now showing 1 - 4 of 4
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    An adjusted network information criterion for model selection in statistical neural network models
    (JMASM, Inc., 2016) Udomboso, C. G.; Amahia, G. N.; Dontwi, I. K.
    In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC) criterion, based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The ANIC improves model selection in more sample sizes than does the NIC.
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    Bio-social correlates of intention to use or not to use contraception: The case of Ghana and Nigeria
    (Union for African Population Studies, 2015) Udomboso, C. G.; Amoateng, A. Y.; Doegah, P. T.
    Based on the 2008 and 2013 Demographic and Health Survey data of Ghana and Nigeria respectively, statistical neural network and logit regression models were used to examine the effects of selected bio-social factors on the intention to use contraception among never married and ever married women in the two countries. The results showed that on the whole, the SNN model identified more biosocial factors affecting the intention to use contraception in the two countries than did the logic model. Educational attainment, exposure to media, and visitation to a health facility affected intention to use contraception significantly and positively in both countries. On the other hand, number of living children, infrequent sexual intercourse, postpartum amenorrhea, opposition to contraception and lack of access to contraceptives negatively affected intention to use contraception. The study findings have underscored the rational nature of the decisions women make in using contraception or not.
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    On some properties of a hetereogeneous transfer function involving symmetric saturated linear (SATLINS) with hyperbolic tangent (TANH) transfer functions
    (JMASM, Inc., 2013-11) Udomboso, C. G.
    For transfer functions to map the input layer of the statistical neural network model to the output layer perfectly, they must lie within bounds that characterize probability distributions. The heterogeneous transfer function, SATLINS_TANH, is established as a Probability Distribution Function (p.d.f), and its mean and variance are shown.
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    Modelling trends in contraception usage in Nigeria and Ghana
    (SAGE Publications, 2018) Udomboso, C. G.; Amoateng, A. Y.
    This study examines trends in contraception usage using Demographic and Health Survey (DHS) data from Nigeria (2013) and Ghana (2008, 2014). We used a cubic spline to estimate values between intervals, analysed using the time-series neural network model and forecasting till 2030. Results show contraception usage increasing with an average rate of 4.4 per cent, desire not to use declining at an average rate of 0.7 per cent and the use of modern contraception increasing at an average rate of 5.1 per cent. Use of traditional contraception is still increasing in Nigeria at a rate of 0.6 per cent but declining in Ghana at a rate of 0.3 per cent. By 2030, injectables would be mostly used, while the withdrawal method will be preferred among those still in favour of the traditional method. These trends show the readiness of the two countries to embrace the use of modern contraception in an effort to promote the campaign for Planned Parenthood and Family Programme.