Boosting Functional Response Models for Location, Scale and Shape with an Application to Bacterial Competition [PDF]
, 2019 We extend Generalized Additive Models for Location, Scale, and Shape (GAMLSS) to regression with functional response. This allows us to simultaneously model point-wise mean curves, variances and other distributional parameters of the response in ...
Brockhaus, Sarah +5 more
core +3 more sources
Media Statistika, 2020 Confidence interval estimation is important in statistical inference for the parameters of the regression model, but the theory of confidence interval estimation for multi-response semiparametric regression model parameters based on the truncated spline ...
Lilik Hidayati +2 more
doaj +1 more source
Measuring the dispersion of rainfall using Bayesian confidence intervals for coefficient of variation of delta-lognormal distribution: a study from Thailand [PDF]
PeerJ, 2019 Since rainfall data series often contain zero values and thus follow a delta-lognormal distribution, the coefficient of variation is often used to illustrate the dispersion of rainfall in a number of areas and so is an important tool in statistical ...
Noppadon Yosboonruang +2 more
doaj +2 more sources
Nonparametric inference in generalized functional linear models [PDF]
, 2015 We propose a roughness regularization approach in making nonparametric inference for generalized functional linear models. In a reproducing kernel Hilbert space framework, we construct asymptotically valid confidence intervals for regression mean ...
Cheng, Guang, Shang, Zuofeng
core +1 more source
Determinants of anemia and hemoglobin concentration in haitian school-aged children [PDF]
, 2015 Anemia diminishes oxygen transport in the body, resulting in potentially irreversible growth and developmental consequences for children. Limited evidence for determinants of anemia exists for school-aged children.
Brown, Sarah +6 more
core +2 more sources
Conditional fiducial models [PDF]
, 2017 The fiducial is not unique in general, but we prove that in a restricted class of models it is uniquely determined by the sampling distribution of the data. It depends in particular not on the choice of a data generating model.
Lindqvist, Bo H., Taraldsen, Gunnar
core +2 more sources
A General Class of Confidence Interval [PDF]
Nature, 1946 AMONG types of statistical inference about unknown parameters statements are possible which have a statistical truth, that is, they are random variables such that within the statistical framework adopted the probability of their being in error is known.
openaire +1 more source
Confidence Interval Construction for Causally Generalized Estimates With Target Sample Summary Information. [PDF]
Stat MedChen Y, Chen G, Yu M.
europepmc +3 more sources
Bayesian Learning for a Class of Priors with Prescribed Marginals [PDF]
, 2006 We present Bayesian updating of an imprecise probability measure, represented by a class of precise multidimensional probability measures. Choice and analysis of our class are motivated by expert interviews that we conducted with modelers in the context ...
Augustin, Thomas +2 more
core +2 more sources
The Bayesian confidence intervals for measuring the difference between dispersions of rainfall in Thailand [PDF]
PeerJ, 2020 The coefficient of variation is often used to illustrate the variability of precipitation. Moreover, the difference of two independent coefficients of variation can describe the dissimilarity of rainfall from two areas or times.
Noppadon Yosboonruang +2 more
doaj +2 more sources