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<item>
  <id>00839391</id>
  <dt>j</dt>
  <an>00839391</an>
  <augroup>
    <au>Koo, Ja-Yong</au>
    <au>Lee, Youngjo</au>
  </augroup>
  <ti>Bivariate B-splines in generalized linear models.</ti>
  <so>J. Stat. Comput. Simulation 50, No.1-2, 119-129 (1994).</so>
  <py>1994</py>
  <pu>Taylor \& Francis, Reading</pu>
  <lagroup>
    <la>EN</la>
  </lagroup>
  <ccgroup>
  </ccgroup>
  <utgroup>
    <ut>bivariate $B$-splines</ut>
    <ut>tensor-product $B$-splines</ut>
    <ut>nonparametric smoothing</ut>
    <ut>Akaike criterion</ut>
    <ut>estimating regression surfaces</ut>
    <ut>continuous covariates</ut>
    <ut>adaptive knot-selection algorithm</ut>
  </utgroup>
  <cigroup>
  </cigroup>
  <ligroup>
    <li>doi:10.1080/00949659408811603</li>
  </ligroup>
  <abgroup>
    <ab>Summary: The bivariate $B$-splines are considered for estimating regression surfaces in generalized linear models. They are useful for describing the surface caused by the joint effect of two continuous covariates. For implementation a simple adaptive knot-selection algorithm is introduced. The performance of bivariate $B$-splines is investigated by numerical studies.</ab>
    <rv></rv>
  </abgroup>
</item>