Novel kernel density estimator based on ensemble unbiased cross-validation

He, Yulin; Ye, Xuan; Huang, De-Fa; Huang, Joshua Zhexue; Zhai, Junhai

doi:10.1016/j.ins.2021.09.045

Cited by 12 publications

(2 citation statements)

References 34 publications

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“…Kernel PDF is a statistical analysis technique used to model the probability distribution of a random, usually continuous variable, using a smooth function (known as the kernel) to approximate the shape of the probability distribution. The aim of the Kernel PDF is to produce a non-parametric estimate of the probability distribution, without assuming a specific shape for the underlying distribution [33]. Moreover, Pearson's correlation and its significance according to the Student's t test were used to assess the relationship between the precipitation and air temperature extreme indices with the SST anomalies [11].…”

Section: Discussionmentioning

confidence: 99%

Trends in Precipitation and Air Temperature Extremes and Their Relationship with Sea Surface Temperature in the Brazilian Midwest

Santos

Machado²,

Biudes

et al. 2023

Atmosphere

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The Brazilian Midwest has significant spatiotemporal variability in terms of precipitation and air temperature, making it more vulnerable to the occurrence of extreme weather events. The objective of this study is to characterize the trend of extreme climatic events regarding precipitation and air temperature in the Brazilian Midwest, and to analyze their relationship with Pacific and Atlantic Sea Surface Temperature anomalies (SSTAs). We used daily precipitation and air temperature data measured at 24 conventional weather stations. Pacific and Atlantic SSTA data were obtained from the Climate Prediction Center. The frequency of hot extremes had increased, while that of cold extremes had decreased significantly, thus highlighting the consistent warming across the Brazilian Midwest. The precipitation extremes had greater variability than the temperature extremes. Precipitation intensity increased in Amazonia, with no change in annual precipitation volume. The precipitation extremes in the Brazilian Savanna, Pantanal, and the Atlantic Forest did not have a well-defined pattern but indicated a trend towards a decrease in days with intense precipitation events. In general, the Equatorial Pacific and Atlantic Ocean (TNAI and TSAI) SSTAs were negatively correlated with precipitation extreme indices and positively correlated with air temperature extreme indices in the Amazon. However, the North Atlantic SSTAs were positively correlated with precipitation and air temperature extreme indices in the Brazilian Savanna and Pantanal. In addition, the Pacific SSTAs were positively correlated with precipitation intensity in the Atlantic Forest. Thus, the variability of the trends of precipitation and air temperature extreme indices in the Brazilian Midwest was observed, and it was surmised that this measure was significantly related to Pacific and Atlantic SSTAs.

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Section: Discussionmentioning

confidence: 99%

Trends in Precipitation and Air Temperature Extremes and Their Relationship with Sea Surface Temperature in the Brazilian Midwest

Santos

Machado²,

Biudes

et al. 2023

Atmosphere

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“…In fact, the distribution of the actual data may be arbitrary, and the probability density function obtained by the parametric estimation methods has great limitations in fitting the data distribution, making it difficult to achieve high-precision interval prediction (Jiang and Nie 2020). Compared with parameter estimation methods, Kernel Density Estimation (KDE) is a nonparametric estimation method that does not require any hypothesis on the distribution of the sample data, has a higher fitting precision and is easy to implement, and thus is widely applied currently (He et al 2021). Han et al (2019) were able to fit the multi-peak, skewness and thick-tail characteristics of the deterministic error distribution of PV power prediction under different intervals well through KDE to complete the PV power interval prediction.…”

Section: Introductionmentioning

confidence: 99%

A hybrid model for point and interval forecasting of agricultural price based on decomposition-ensemble and KDE

Zhang,

et al. 2023

Preprint

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Accurate and reliable price forecasting of agricultural products is significant for promoting the production and distribution of agricultural products, optimizing resource allocation and improving market efficiency. Due to the non-stationary feature in agricultural price, based on decomposition integration and kernel density estimation(KDE), this paper proposes a hybrid model for agricultural price forecasting that can quantify the uncertainty of potential forecasts by converting traditional point forecasts into interval forecasts. Firstly, the price sequence is decomposed through variational modal decomposition (VMD) determined by energy entropy (EE); secondly, K-means clustering is used to reconstruct the intrinsic modal functions (IMFs) into low-frequency components and high-frequency components, forecasted by different methods. In addition, adaptive kernel density estimation (AKDE) is established through dynamic window and whale optimization algorithm (WOA), which is used to construct prediction interval with the residual signal obtained by VMD. Finally, to validate the superiority of the proposed model, comparative experiments with three different datasets are conducted. The results show that prediction performance of the proposed model is better than other models in both point forecasts and interval forecasts, and it can provide more accurate uncertainty information to agricultural participants.

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A hybrid model for point and interval forecasting of agricultural price based on the decomposition-ensemble and KDE

Zhang,

et al. 2024

Soft Comput

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Novel kernel density estimator based on ensemble unbiased cross-validation

Cited by 12 publications

References 34 publications

Trends in Precipitation and Air Temperature Extremes and Their Relationship with Sea Surface Temperature in the Brazilian Midwest

Trends in Precipitation and Air Temperature Extremes and Their Relationship with Sea Surface Temperature in the Brazilian Midwest

A hybrid model for point and interval forecasting of agricultural price based on decomposition-ensemble and KDE

A hybrid model for point and interval forecasting of agricultural price based on the decomposition-ensemble and KDE

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