02078naa a2200217 a 450000100080000000500110000800800410001902400570006010000220011724500820013926000090022152013870023065000170161765000320163465300270166665300160169370000200170970000220172970000210175177300880177221519662023-02-27       2017    bl uuuu     u00u1 u    #d7 ahttp://dx.doi.org/10.1080/03610926.2016.11524852DOI1 aPARAIBA, C. C. M.  aTruncated location-scale non linear regression models.h[electronic resource]  c2017  aABSTRACT: We present a class of truncated non linear regression models for location and scale where the truncated nature of the data is incorporated into the statistical model by assuming that the response variable follows a truncated distribution. The location parameter of the response variable is assumed to be modeled by a continuous non linear function of covariates and unknown parameters. In addition, the proposed model also allows for the scale parameter of the responses to be characterized by a continuous function of the covariates and unknown parameters. Three particular cases of the proposed models are presented by considering the response variable to follow a truncated normal, truncated skew normal, and truncated beta distribution. These truncated non linear regression models are constructed assuming fixed known truncation limits and model parameters are estimated by direct maximization of the log-likelihood using a non linear optimization algorithm. Standardized residuals and diagnostic metrics based on the cases deletion are considered to verify the adequacy of the model and to detect outliers and influential observations. Results based on simulated data are presented to assess the frequentist properties of estimates, and a real data set on soil-water retention from the Buriti Vermelho River Basin database is analyzed using the proposed methodology.  aDiagnóstico  aRetenção de Água no Solo  aRegressão Não-Linear  aTruncamento1 aDINIZ, C. A. R.1 aMAIA, A. de H. N.1 aRODRIGUES, L. N.  tCommunications in Statistics: Theory and Methodsgv. 46, n. 15, p. 7355-7374, 2017.