Results 11 to 20 of about 115 (106)
Majalah Ilmiah Matematika dan Statistika, 2022 Forecasting is a technique for estimating a value on a particular object in the future by paying attention to past data. This forecasting uses the Exponential Smoothing models because the data used is in accordance with the model.
Muhammad Marizal, Fikha Mutiarani
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Majalah Ilmiah Matematika dan Statistika, 2022 The fuzzy time series method for forecasting continues to develop over time. This research discusses fuzzy time series, which considers two factors for high order using interval partitioning based on interval ratio with long relation construction for ...
Etna Vianita +2 more
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A novel approach to compare the spectral densities of some uncorrelated cyclostationary time series
Alexandria Engineering Journal, 2022 Our primary objective in this article is to compare the spectral densities of some cyclostationary time series. By using the limiting distributions of the discrete Fourier transform, a novel approach is introduced to determine whether the spectral ...
Mohammad Reza Mahmoudi +4 more
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Locf imputation for Astra Agro Lestari Tbk. (Indonesia) and Anadolu Group (Turkey) stock
Majalah Ilmiah Matematika dan Statistika, 2022 This study aims to apply time series graphs on stock of Astra Agro Lestari Tbk. and Anadolu Group with last observation carried forward (LOCF) imputation. The imputation was used because the data for the two companies had missing values on several dates.
Fadhlul Mubarak +2 more
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Peramalan nilai tukar rupiah terhadap dollar Amerika menggunakan model ARIMA
Majalah Ilmiah Matematika dan Statistika, 2023 The exchange rate of the Rupiah against the currencies of other countries is one of the factors in identifying the condition of an economic condition.
Andreas Rony Wijaya
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Volatility filtering in estimation of kurtosis (and variance)
Dependence Modeling, 2019 The kurtosis of the distribution of financial returns characterized by high volatility persistence and thick tails is notoriously difficult to estimate precisely.
Anatolyev Stanislav
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Prediction of time series by statistical learning: general losses and fast rates
Dependence Modeling, 2013 We establish rates of convergences in statistical learning for time series forecasting. Using the PAC-Bayesian approach, slow rates of convergence √ d/n for the Gibbs estimator under the absolute loss were given in a previous work [7], where n is the ...
Alquier Pierre +2 more
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Time series modelling of the Kobe‐Osaka earthquake recordings
International Journal of Mathematics and Mathematical Sciences, Volume 29, Issue 8, Page 467-479, 2002., 2002 A problem of great interest in monitoring a nuclear test ban treaty (NTBT) is related to interpreting properly the differences between a waveform generated by a nuclear explosion and that generated by an earthquake. With a view of comparing these two types of waveforms, Singh (1992) developed a technique for identifying a model in time domain ...
N. Singh +2 more
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Majalah Ilmiah Matematika dan Statistika, 2022 The Infant Mortality Rate (IMR) is fundamental indicator that reflects the health status in the surrounding community. The Infant Mortality Rate is still categorized as high in Indonesia.
Muhammad Marizal +1 more
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Parallelization algorithms for modeling ARM processes
International Journal of Stochastic Analysis, Volume 13, Issue 4, Page 393-410, 2000., 2000 AutoRegressive Modular (ARM) processes are a new class of nonlinear stochastic processes, which can accurately model a large class of stochastic processes, by capturing the empirical distribution and autocorrelation function simultaneously. Given an empirical sample path, the ARM modeling procedure consists of two steps: a global search for locating ...
Benjamin Melamed, Santokh Singh
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