[HTML][HTML] Comparison of methods of estimating missing values in time series
This paper proposes new methods of estimating missing values in time series data while
comparing them with existing methods. The new methods are based on the row, column and …
comparing them with existing methods. The new methods are based on the row, column and …
[PDF][PDF] Kalman filter algorithm versus other methods of estimating missing values: time series evidence
AO Agbailu, A Seno, OO Clement - Studies, 2020 - abjournals.org
Ideally, we think data are carefully collected and have regular patterns with no missing
values, but in reality, this does not always happen. This study examines four (4) methods …
values, but in reality, this does not always happen. This study examines four (4) methods …
Application of non-parametric regression in estimating missing daily rainfall data
Most daily rainfall time series data are too short and/or possess missing records hindering
them to perform reliable and meaningful analyses. Robust locally weighted scatter smoother …
them to perform reliable and meaningful analyses. Robust locally weighted scatter smoother …
Development of risk-based groundwater operating rules: A case study of Siloam Village, South Africa
R Makungo - 2019 - univendspace.univen.ac.za
This study developed operating rules for groundwater supply from a probabilistic (risk-
based) approach. Groundwater supply systems are often operated without relating …
based) approach. Groundwater supply systems are often operated without relating …
تأثير فقدان إحدى مشاهدات المتغير المستقل وموقعها في تحليل الانحدار البسيط
علي درب كسار, عفاف صالح الحاني - Journal of Economics …, 2011 - jeasiq.uobaghdad.edu.iq
يهدف البحث إلى تسليط الضوء على أهم معالجات مشكلة فقدان بيانات السلسلة الزمنية وتأثيرها في
تحليل الانحدار الخطي البسيط. ويتناول البحث تأثير فقدان المشاهدات في المتغير المستقل فقط …
تحليل الانحدار الخطي البسيط. ويتناول البحث تأثير فقدان المشاهدات في المتغير المستقل فقط …