The ability to localize in changing environments is essential for robust long-term navigation. Robots operating over extended periods of time must be able to handle substantial appearance changes. In this paper, we investigate the problem of efficiently coping with seasonal changes in online localization. We propose an online lazy data association approach for matching streams of incoming image...

We demonstrate the poor performance, with seasonal data, of existing methods for endogenously dating multiple structural breaks. Motivated by iterative nonparametric techniques, we present a new approach for estimating parametric structural break models that performs well. We suggest that iterative estimation methods are a simple but important feature of this approach to seasonal modelling. The...

This paper considers simultaneous modelling of seasonality, slowly changing unconditional variance and conditional heteroskedasticity in high-frequency nancial returns. A new approach, called a seasonal SEMIGARCH model, is proposed to perform this by introducing multiplicative seasonal and trend components into the GARCH model. A data-driven semiparametric algorithm is developed for estimating ...

With the increasing temporal resolution of medium spatial resolution data, seasonal features are becoming more readily available for land cover characterization. However, in the tropical regions, images can be severely contaminated by clouds during the rainy season and fires during the dry season, with possible effects to seasonal features. In this study, we evaluated the performance of seasona...

to study the seasonal variation in the characteristics of the azarbaijani buffalo semen, three 2-4-year-oldbulls of azarbaijani water buffaloes, kept in the buffalo breeding center, in urmia, northwest of iran, wereselected. semen samples were collected once a week for a period of one year using artificial vagina and abuffalo cow as a dummy. semen volume, colour, ph and motility and spermatozoa...

Introduction Conclusions References Tables Figures Back Close Abstract Introduction Conclusions References Tables Figures Back Close Abstract A seasonal-trend decomposition technique based on a locally-weighted regression smoothing (Loess) approach has been used to decompose monthly ozone concentrations at Mace Head (Ireland) into trend, seasonal and irregular components. The trend component sh...

This paper deals with the analysis of the number of tourists travelling to the Canary Islands by means of using different seasonal statistical models. Deterministic and stochastic seasonality is considered. For the latter case, we employ seasonal unit roots and seasonally fractionally integrated models. As a final approach, we also employ a model with possibly different orders of integration at...

This research is dedicated to the study of periodic characteristics of periodically correlated time series such as seasonal means, seasonal variances and autocovariance functions. Two bootstrap methods are used: the extension of the usual Moving Block Bootstrap (EMBB) and the Generalized Seasonal Block Bootstrap (GSBB). The first approach is proposed, because the usual MBB does not preserve the...

Recent developments in dynamical seasonal forecasting of potential relevance to agricultural management are discussed. These developments emphasize the importance of using a fully probabilistic approach at all stages of the forecasting process, from the dynamical ocean–atmosphere models used to predict climate variability at seasonal and interannual time scales, through the models used to downs...