Intelligent autonomous navigation in a large-scale and unknown indoor environment is an important problem in mobile robotics. For a car-like mobile robot with a racing car platform, the movement control concept is similar to that of a car. The autonomous features enable robots to control own motion without human interference. Three autonomous features are addressed in this thesis; obstacle avoi...

‎In this article‎, ‎we develop two nonparametric smoothing estimators for parameter of a time-variant parametric model‎. ‎This parameter can be from any parametric family or from any parametric or semi-parametric regression model‎. ‎Estimation is based on a two-step procedure‎, ‎in which we first get the raw estimate of the parameter at a set of disjoint time...

Quantitative fatty acid signature analysis has become an important method of diet estimation in ecology, especially marine ecology. Controlled feeding trials to validate the method and estimate the calibration coefficients necessary to account for differential metabolism of individual fatty acids have been conducted with several species from diverse taxa. However, research into potential refine...

In the context of ridge regression, the estimation of ridge (shrinkage) parameter plays an important role in analyzing data. Many efforts have been put to develop skills and methods of computing shrinkage estimators for different full-parametric ridge regression approaches, using eigenvalues. However, the estimation of shrinkage parameter is neglected for semiparametric regression models. The m...

‎Recently‎, ‎a new distribution‎, ‎named as extended generalized exponential distribution‎, ‎has been introduced by Kundu and Gupta (2011). ‎In this paper‎, ‎we consider the extended generalized exponential distribution with known shape parameters α and β. ‎At first‎, ‎the exact expressions for marginal and product moments of o...

 Minimax estimation problems with restricted parameter space reached increasing interest within the last two decades Some authors derived minimax and admissible estimators of bounded parameters under squared error loss and scale invariant squared error loss In some truncated estimation problems the most natural estimator to be considered is the truncated version of a classic...

Outliers are observations that significantly different from the other in a dataset. These types of asymmetric nature due to lack symmetry. The estimation cumulative distribution function (CDF) is an important statistical measure commonly discussed for symmetric datasets. However, CDF case dataset not much-explored topic. In this article, we use calibration methodology with auxiliary information...

The Averaged One Dependency Estimator (AODE) is integrated all possible Super-Parent-One-Dependency Estimators (SPODEs) and estimates class conditional probabilities by averaging them. In an AODE network some redundant SPODEs maybe result in some bias of classifiers, as a consequence, it could reduce the classification accuracy substantially. In this paper, a kind of MDL metrics is used to sele...