Results 41 to 50 of about 361,494 (239)
Adaptive Blind Multiuser Detection over Flat Fast Fading Channels Using Particle Filtering
EURASIP Journal on Wireless Communications and Networking, 2005 We propose a method for blind multiuser detection (MUD) in synchronous systems over flat and fast Rayleigh fading channels. We adopt an autoregressive-moving-average (ARMA) process to model the temporal correlation of the channels.
Huang Yufei +4 more
doaj +1 more source
A new energy-balance approach to linear filtering for estimating effective radiative forcing from temperature time series [PDF]
Advances in Statistical Climatology, Meteorology and Oceanography, 2020 Reliable estimates of historical effective radiative forcing (ERF) are important for understanding the causes of past climate change and for constraining predictions of future warming.
D. P. Cummins +3 more
doaj +1 more source
Penerapan Model Arima dalam Peramalan Jumlah Pelanggan Wifi Internet di Surabaya [PDF]
, 2018 PT. Exas adalah Perusahaan informasi dan komunikasi serta penyedia jasa dan jaringan telekomunikasi secara lengkap di Indonesia. PT. Exas merupakan salah satu BUMN (Badan Usaha Milik Negara) yang dimiliki oleh pemerintah Indonesia dan salah satu asset ...
HENDRIYANTO, R. (RENDRA)
core
Energy Science &Engineering, EarlyView.ABSTRACT To promote the development of renewable energy, China re‐implemented the Chinese Certified Emission Reduction (CCER) policy in 2023. This study explores certificated CO2 and air pollutants (i.e., NOx, SO2 and particulate matter (PM)) emissions reductions from China's solar thermal power (STP) industry at national scale and conducts the ...
Yun Li +3 more
wiley +1 more source
Forecasting House Prices: The Role of Market Interconnectedness
Journal of Forecasting, EarlyView.ABSTRACT While the existing research uncovers interconnections between various housing markets, it largely ignores the question of whether such linkages can improve house price predictions. To address this issue, we proceed in two steps. First, we forecast disaggregated house price growth rates from Australia and China to determine whether ...
Zac Chen +3 more
wiley +1 more source
Intraday Functional PCA Forecasting of Cryptocurrency Returns
Journal of Forecasting, EarlyView.ABSTRACT We study the functional PCA (FPCA) forecasting method in application to functions of intraday returns on Bitcoin. We show that improved interval forecasts of future return functions are obtained when the conditional heteroscedasticity of return functions is taken into account.
Joann Jasiak, Cheng Zhong
wiley +1 more source
Evaluating Forecasts at Multiple Horizons: An Extension of the Diebold–Mariano Approach
Journal of Forecasting, EarlyView.ABSTRACT Forecast accuracy tests are fundamental tools for comparing competing predictive models. The widely used Diebold–Mariano (DM) test assesses whether differences in forecast errors are statistically significant. However, its standard form is limited to pairwise comparisons at a single forecast horizon.
Andrew Grant +2 more
wiley +1 more source
On nonnegative solutions of SDDEs with an application to CARMA processes
Modern Stochastics: Theory and Applications, 2021 This note provides a simple sufficient condition ensuring that solutions of stochastic delay differential equations (SDDEs) driven by subordinators are nonnegative.
Mikkel Slot Nielsen, Victor Rohde
doaj +1 more source
A Guide to Solar Power Forecasting using ARMA Models
, 2018 We describe a simple and succinct methodology to develop hourly auto-regressive moving average (ARMA) models to forecast power output from a photovoltaic solar generator.
Pozo, David, Singh, Bismark
core +1 more source
Re-Transformation of Power Transformation for ARMA(p, q) Model - Simulation Study
Korean Journal of Applied Statistics, 2015 For time series analysis, power transformation (especially log-transformation) is widely used for variance stabilization or normalization for stationary ARMA(p, q) model. A simple and naive back transformed forecast is obtained by taking the inverse function of expectation. However, this back transformed forecast has a bias.
Jun-Hoon Kang, Key-Il Shin
openaire +2 more sources