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2021 ◽  
Vol 4 (2) ◽  
pp. 163-173
Author(s):  
Arif Rahman ◽  
Muhammad Hasbi
Keyword(s):  

Kebijakan pengendalian inflasi memiliki dampak yang cukup baik pada perekonomian Indonesia yang tumbuh hingga 5-6 persen pada periode 2010-2016. Namun, pertumbuhan ekonomi tersebut ternyata didominasi oleh wilayah Jakarta, Bogor, Depok, Tangerang, dan Bekasi (Jabodetabek) yang menyumbang hingga 20 persen dari total PDB Indonesia. Survei Biaya Hidup (SBH) 2012 menunjukkan bahwa wilayah Jabodetabek memiliki bobot inflasi terbesar diantara seluruh wilayah di Indonesia, yakni mencapai 35 persen, sehingga dengan melakukan analisis terhadap inflasi di wilayah Jabodetabek diharapkan dapat menggambarkan keadaan inflasi secara nasional. Dalam menganalisis inflasi daerah yang berdekatan, maka aspek spasial perlu diperhitungkan dalam pemodelan. Oleh karena itu, dalam pemodelan inflasi Jabodetabek digunakan metode STARMA dan GSTARMA untuk memasukkan aspek spasial. Hasil penelitian menunjukkan model STAR (11) dengan pembobot normalisasi korelasi silang merupakan model terbaik daripada model GSTAR. Hasil ini disimpulkan dengan membandingkan rata-rata RMSE dari setiap model dan STAR (11) memiliki nilai RMSE terkecil.


2020 ◽  
Vol 8 (1) ◽  
pp. 59
Author(s):  
GREKOU Gahié Lopez

This paper tests the hypothesis of double deficit in Côte d'Ivoire in non-linear aid framework, using an autoregressive smooth transition model (STAR). The main results validate the hypothesis of double deficit in Côte d' Ivoire. The effect of current balance on budget balance is greater than budget balance on current balance. Moreover, the rapid effects of current account instability on fiscal balance reveal the lack of expectation by economic agents that leads to current account deterioration compared to the deterioration of budget balance.  Thus, economic policies aimed at influencing the effect on current balance would be more effective than those aimed at the effect on budget balance. In other words, Ivorian economy adopts a Keynesian performance in the event of current account shocks and performance that tend to be more or less Ricardian in presence of fiscal policy shock.


2020 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Lorne N. Switzer ◽  
Alan Picard

While the average annual small-cap premia for the US and Canada are substantial over long horizons, there is considerable time variation of this premium within and across these countries. For the US, during expansions, the average annualized premium is a sizable 5.44%, while during recessions, there is a small-cap discount of 6.23%. The differentials are less pronounced in Canada. This paper investigates the hypothesis that the variation of the small-cap premium is related to macroeconomic and financial variables that can be captured by a nonlinear time series econometric model, i.e., the smooth transition autoregressive model (STAR model), with different factor sets across regimes between and countries. The regimes reflect expansionary vs. contractionary phases of the business cycle. For the Canadian small-cap premium, an augmented factor model that includes US factors dominates a purely domestic factor model, which is consistent with integrated markets.


2019 ◽  
Vol 1 (2) ◽  
pp. 115
Author(s):  
Wahidah Sanusi ◽  
Maya Sari Wahyuni ◽  
Rahmat Setiawan

Abstrak. Model Space Time Autoregressive (STAR) merupakan data deret waktu yang mempunyai keterkaitan antar lokasi (space time). Tujuan dari penelitian ini adalah untuk mendapatkan model STAR yang sesuai dengan data jumlah penderita penyakit DBD di Provinsi Sulawesi Barat serta memperoleh data hasil ramalan untuk beberapa bulan kedepan. Data yang digunakan merupakan data bulanan penderita DBD di lima lokasi yaitu Kota Mamuju, Kabupaten Majene, Kabupaten Polmas, Kabupaten Mamuju Tengah, dan Kabupaten Mamuju Utara pada Januari 2014 sampai Juli 2016. Pendugaan parameter model STAR menggunakan metode kuadrat terkecil (MKT). Model STAR yang sesuai dengan data jumlah penderita penyakit DBD di Provinsi Sulawesi Barat adalah model STAR5(11). Pembobot yang digunakan merupakan bobot lokasi seragam. Pada hasil pengecekan parameter penduga dengan menggunakan bobot lokasi seragam didapatkan tiga model. Hal ini dilihat dari adanya pengaruh yang nyata terhadap lokasi yang berdekatan. Hasil ramalan dengan model STAR5(11) tentang jumlah penderita penyakit DBD di Provinsi Sulawesi Barat untuk dua bulan kedepan yaitu bulan Agustus sampai September 2016.Kata Kunci: Model STAR, ARIMA, Autoregressive, Deret WaktuAbstract. The Space Time Autoregressive (STAR) model is a time series data that has a link between locations (space time). The purpose of this study was to obtain a STAR model that was in accordance with the data on the number of dengue fever patients in West Sulawesi Province and also the forecast data for the next few months. Data in the form of DHF data in five locations, namely Mamuju City, Majene Regency, Polmas District, Central Mamuju Regency, and North Mamuju Regency from January 2014 to July 2016. STAR Estimation parameter model uses vertical squares (MKT) method. The STAR model that matches the data on the number of DHF patients in West Sulawesi Province is the STAR5 model (11). The weighting is a uniform location. In the estimator checking results using uniform location weight of three models. Things that happen between others. Forecast results with the STAR5 (11) model on the number of dengue fever patients in West Sulawesi Province for the next two months, namely August to September 2016, namely 9 people for Mamuju City and 12 people for Polman Regency.Keywords: STAR Model, ARIMA, Autoregressive, Time Series


2018 ◽  
Vol 868 (2) ◽  
pp. 92 ◽  
Author(s):  
Sandro Tacchella ◽  
Sownak Bose ◽  
Charlie Conroy ◽  
Daniel J. Eisenstein ◽  
Benjamin D. Johnson

2018 ◽  
Vol 19 (1) ◽  
pp. 35-38
Author(s):  
Khafsah Joebaedi
Keyword(s):  

Model STAR (1;1) atau model Space Time Auto Regresi(1;1) adalah salah satu bentuk model yang melibatkan lokasi dan waktu. Model STAR(1;1) stasioner dapat digunakan untuk prakiraan observasi di suatu lokasi pada waktu mendatang berdasarkan satu waktu sebelumnya dari lokasinya sendiri dan lokasi-lokasi lain disekitarnya. Penerapan model STAR(1;1) pada data stasioner produktivitas teh menunjukkan bahwa nilai Eigen dari matriks parameter model STAR(1;1) bernilai lebih kecil dari 1. Hal ini menunjukkan bahwa parameter model STAR(1;1) untuk data produktivitas teh tersebut memenuhi syarat stasioner.


2017 ◽  
Vol 609 ◽  
pp. A30 ◽  
Author(s):  
C. Schreiber ◽  
D. Elbaz ◽  
M. Pannella ◽  
L. Ciesla ◽  
T. Wang ◽  
...  

We present a new, publicly available library of dust spectral energy distributions (SEDs). These SEDs are characterized by only three parameters: the dust mass (Mdust), the dust temperature (Tdust), and the mid-to-total infrared color (IR8 ≡ LIR/L8). The latter measures the relative contribution of polycyclic aromatic hydrocarbon (PAH) molecules to the total infrared luminosity. We used this library to model star-forming galaxies at 0.5 < z < 4 in the deep CANDELS fields, using both individual detections and stacks of Herschel and ALMA imaging, and extending this sample to z = 0 using the Herschel Reference Survey. At first order, the dust SED of a galaxy was observed to be independent of stellar mass, but evolving with redshift. We found trends of increasing Tdust and IR8 with redshift and distance from the SFR–M∗ main sequence, and quantified for the first time their intrinsic scatter. Half of the observed variations of these parameters was captured by the above empirical relations, and after subtracting the measurement errors we found residual scatters of ΔTdust/Tdust = 12% and Δlog IR8 = 0.18 dex. We observed second order variations with stellar mass: massive galaxies (M∗ > 1011M⊙) at z ≤ 1 have slightly lower temperatures indicative of a reduced star formation efficiency, while low mass galaxies (M∗ < 1010M⊙) at z ≥ 1 showed reduced PAH emission, possibly linked to their lower metallicities. Building on these results, we constructed high-fidelity mock galaxy catalogs to predict the accuracy of infrared luminosities and dust masses determined using a single broadband measurement. Using a single James Webb Space Telescope (JWST) MIRI band, we found that LIR is typically uncertain by 0.15 dex, with a maximum of 0.25 dex when probing the rest-frame 8 μm, and this is not significantly impacted by typical redshift uncertainties. On the other hand, we found that ALMA bands 8 to 7 and 6 to 3 measured the dust mass at better than 0.2 and 0.15 dex, respectively, and independently of redshift, while bands 9 to 6 only measured LIR at better than 0.2 dex at z > 1, 3.2, 3.8, and 5.7, respectively. Starburst galaxies had their LIR significantly underestimated when measured by a single JWST or ALMA band, while their dust mass from a single ALMA band were moderately overestimated. This dust library and the results of this paper can be used immediately to improve the design of observing proposals, and interpret more accurately the large amount of archival data from Spitzer, Herschel and ALMA.


2017 ◽  
Vol 609 ◽  
pp. A29 ◽  
Author(s):  
S. Goriely ◽  
L. Siess

Context. S-process elements are observed at the surface of low- and intermediate-mass stars. These observations can be explained empirically by the so-called partial mixing of protons scenario leading to the incomplete operation of the CN cycle and a significant primary production of the [see formula in PDF] neutron source. This scenario has been successful in qualitatively explaining the s-process enrichment in AGB stars. Even so, it remains difficult to describe both physically and numerically the mixing mechanisms taking place at the time of the third dredged-up between the convective envelope and the underlying C-rich radiative layer Aims. We aim to present new calculations of the s-process nucleosynthesis in AGB stars testing two different numerical implementations of chemical transport. These are based on a diffusion equation which depends on the second derivative of the composition and on a numerical algorithm where the transport of species depends linearly on the chemical gradient. Methods. The s-process nucleosynthesis resulting from these different mixing schemes is calculated with our stellar evolution code STAREVOL which has been upgraded to include an extended s-process network of 411 nuclei. Our investigation focuses on a fiducial 2 M⊙, [Fe/H] = −0.5 model star, but also includes four additional stars of different masses and metallicities. Results. We show that for the same set of parameters, the linear mixing approach produces a much larger 13C-pocket and consequently a substantially higher surface s-process enrichment compared to the diffusive prescription. Within the diffusive model, a quite extreme choice of parameters is required to account for surface s-process enrichment of 1–2 dex. These extreme conditions can not, however, be excluded at this stage. Conclusions. Both the diffusive and linear prescriptions of the overshoot mixing are suited to describe the s-process nucleosynthesis in AGB stars provided the profile of the diffusion coefficient below the convective envelope is carefully chosen. Both schemes give rise to relatively similar distributions of s-process elements, but depending on the parameters adopted, some differences may be obtained. These differences are in the element distribution, and most of all in the level of surface enrichment.


2016 ◽  
Vol 8 (2) ◽  
pp. 81
Author(s):  
Kankan Kankan Parmikanti ◽  
Khafsah Joebaedi ◽  
Iin Irianingsih

Lately when rainfall in West Java is quite high, the problem of flooding caused by overflowing of the river has always been a trending topic of regional leaders. Whatever the causes of flooding, be it because a lot of waste dumped in rivers or due to illegal logging of trees in the forest, the river water discharge increased rapidly, and overflowed into public housing. Based on the above, it should be made a model that can predict the water discharge of the river from time to time in various locations in West Java. In this paper will be presented studies Space Time Auto Regression models STAR (1,1) to model the problem of water discharge some rivers in West Java, which can be useful for predicting the discharge of river water in the future. By using Least Squares Method as predictors for the parameters, as well as assuming a uniform weighting matrix, the result that the water discharge of a river in addition affected by the river water flow at an earlier time, it is also influenced by the discharge of river water around.


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