<div dir="ltr"><div class="gmail_default" style="font-family:verdana,sans-serif;font-size:small">Prezados(as),</div><div class="gmail_default" style="font-family:verdana,sans-serif;font-size:small"><br></div><div class="gmail_default" style="font-family:verdana,sans-serif;font-size:small">Convidamos a todos os interessados a participar. Obrigado, abs.</div><div class="gmail_default" style="font-family:verdana,sans-serif;font-size:small">Ronaldo</div><div class="gmail_default" style="font-family:verdana,sans-serif;font-size:small"><br></div><div class="gmail_default" style="font-family:verdana,sans-serif;font-size:small"><div class="gmail_default" style="color:rgb(34,34,34);font-size:small;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;font-family:verdana,sans-serif">Seminários em Análise de Dados em Alta Dimensão. <AD,AD></div><div class="gmail_default" style="color:rgb(34,34,34);font-size:small;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;font-family:verdana,sans-serif">Sala: 221 IMECC, as 13hs, 13/06/2018</div><div class="gmail_default" style="color:rgb(34,34,34);font-size:small;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;font-family:verdana,sans-serif"><br></div><div class="gmail_default" style="color:rgb(34,34,34);font-size:small;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;font-family:verdana,sans-serif"><span style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:16px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">A spline-based approach to spatially confounded linear regression of geostatistical data</span></div><div class="gmail_default" style="color:rgb(34,34,34);font-size:small;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial;font-family:verdana,sans-serif">(Guilherme Ludwig, DE, IMECC-UNICAMP)<br style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:16px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial"><br style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:16px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial"><span style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:16px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">Abstract: For spatial linear regression, the traditional approach is to use a parametric linear mixed-effects model such that spatial dependence is captured as a spatial random effect; this effect is often assumed to be a Gaussian process with mean zero and a parametric covariance function. Spline surfaces can be used as an alternative approach to capture spatial variability, giving rise to a semiparametric method that does not require the specification of a parametric covariance structure. The spline component in such a semiparametric method, however, impacts the estimation of the regression coefficients. In this talk, we investigate such an impact in spatial linear regression with spline-based spatial effects. Statistical properties of the regression coefficient estimators are established under the model assumptions of the traditional spatial linear regression. We also develop a method to choose the tuning parameter for the smoothing splines that is tailored toward drawing inference about the regression coefficients. Further, we examine the empirical properties of the regression coefficient estimators under spatial confounding. A data example in precision agriculture research regarding soybean yield in relation to field conditions is presented for illustration.</span><br></div><br class="gmail-Apple-interchange-newline"><br></div><br clear="all"><div><br></div>-- <br><div class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div><div>Ronaldo Dias</div>Professor<div>Dept. of Statistics-IMECC, UNICAMP</div><div><a href="http://www.ime.unicamp.br/~dias" target="_blank">www.ime.unicamp.br/~dias</a></div><div><br></div></div></div></div>
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