scholarly journals Some Results on ℓ1 Polynomial Trend Filtering

Econometrics ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 33
Author(s):  
Hiroshi Yamada ◽  
Ruixue Du
Keyword(s):  
Polynomial Trend

scholarly journals Peramalan Jumlah Populasi Sapi Potong di Kalimantan Selatan Menggunakan Metode Moving Average, Exponential Smoothing dan Trend Analysis

2019 ◽  
Vol 6 (1) ◽  
pp. 41
Author(s):  
Jaka Darma Jaya
Keyword(s):  
Trend Analysis ◽  
Mean Squared Error ◽  
Moving Average ◽  
Exponential Smoothing ◽  
Mean Absolute Percentage Error ◽  
Percentage Error ◽  
Absolute Percentage Error ◽  
Polynomial Trend ◽  
Squared Error

Perkembangan produksi daging sapi di Indonesia selama 30 tahun terakhir secara umum cenderung meningkat. Kebutuhan daging sapi di Indonesia masih belum bisa dicukupi oleh supply domestik, sehingga diperlukan impor daging sapi dari luar negeri.  Diperlukan kajian tentang proyeksi ketersediaan populasi sapi potong di masa mendatang agar diambil kebijakan yang tepat dalam menjaga stabilitas dan keterpenuhan supply daging nasional.  Penelitian ini bertujuan untuk melakukan peramalan jumlah populasi sapi potong menggunakan 3 (tiga) metode peramalan yaitu metode moving average, exponential smoothing dan trend analysis.  Hasil peramalan ini selanjutnya diukur akurasinya menggunakan MAD (Mean Absolud Deviation), MSE (Mean Squared Error) dan MAPE (Mean Absolute Percentage Error).  Proyeksi populasi sapi potong pada tahun 2019 (periode berikutnya) menggunakan 3 metode peramalan adalah: 195.100 (moving average); 218.225 (exponential smooting) dan 262.899 (trend analysis). Pengukuran akurasi menggunakan MAD, MSE dan MAPE menunjukkan bahwa metode peramalan jumlah populasi sapi potong yang paling akurat adalah peramalan menggunakan metode polynomial trend analysis (MAD 14.716,12;  MSE 327.282.084,17; dan MAPE 0,09) karena memiliki tingkat kesalahan yang lebih kecil dibandingkan hasil peramalan menggunakan metode moving average dan exponential smoothing.

scholarly journals The Application of Polynomial Trend Term Removing in the Acoustic Wave Gauge Data Processing

2018 ◽  
Vol 452 ◽  
pp. 042054
Author(s):  
Ying Yang ◽  
Li Hui ◽  
Xiangtao Ran ◽  
Zhi Wang ◽  
Yang Zhou ◽  
...  
Keyword(s):  
Acoustic Wave ◽  
Data Processing ◽  
Polynomial Trend ◽  
Gauge Data

Determination of a polynomial trend of optimal complexity

Cybernetics ◽  
1977 ◽  
Vol 13 (2) ◽  
pp. 300-303
Author(s):  
G. A. Akinfiev
Keyword(s):  
Optimal Complexity ◽  
Polynomial Trend

UNIT ROOT SEASONAL AUTOREGRESSIVE MODELS WITH A POLYNOMIAL TREND OF HIGHER DEGREE

2001 ◽  
Vol 17 (2) ◽  
pp. 357-385 ◽  
Author(s):  
Seiji Nabeya
Keyword(s):  
Asymptotic Behavior ◽  
Generating Functions ◽  
Unit Root ◽  
Autoregressive Models ◽  
Sample Period ◽  
Limiting Distributions ◽  
Polynomial Degree ◽  
Polynomial Trend ◽  
Autoregressive Parameter ◽  
Simulation Results

Seasonal autoregressive models with a polynomial trend of higher degee are treated. In the unit root case, the limiting distribution of the normalized least squares estimator for the autoregressive parameter and that of the corresponding t-statistic are discussed as the length of the sample period tends to infinity. In the case where the polynomial trend has the second or third degree, the joint moment generating functions associated with these limiting distributions are derived, and some simulation results are reported. The asymptotic behavior of these limiting distributions is discussed when the polynomial degree or the number of seasons tends to infinity.

Efficiency of least-squares-estimation of polynomial trend when residuals are autocorrelated

1994 ◽  
Vol 45 (3) ◽  
pp. 267-271 ◽  
Author(s):  
Ralf Busse ◽  
Roland Jeske ◽  
Walter Krämer
Keyword(s):  
Least Squares ◽  
Least Squares Estimation ◽  
Polynomial Trend

scholarly journals Control of Tall Fescue in Kentucky Bluegrass Turf with Selective Herbicides

HortScience ◽  
1990 ◽  
Vol 25 (4) ◽  
pp. 449-451
Author(s):  
J.M. Goatley ◽  
A.J. Powell ◽  
W.W. Witt ◽  
M. Barrett
Keyword(s):  
Tall Fescue ◽  
Festuca Arundinacea ◽  
Poa Pratensis ◽  
Kentucky Bluegrass ◽  
Response Curves ◽  
Trend Analyses ◽  
Polynomial Trend ◽  
Selective Control ◽  
Quadratic Response ◽  
Potential Use

Chlorsulfuron, diclofop, and sulfometuron were evaluated for potential use in selective control of tall fescue (Festuca arundinacea Schreb.) in Kentucky bluegrass (Poa pratensis L.). Polynomial trend analyses indicated highly significant linear and quadratic response curves for percentage of tall fescue reduction for each herbicide. Fall and spring treatments with chlorsulfuron and diclofop provided significant tall fescue control, with slight to moderate initial Kentucky bluegrass phytotoxicity. Fall and spring applications of sulfometuron resulted in excellent tall fescue control, but initial Kentucky bluegrass damage was severe and would be unacceptable for high maintenance turf. Chemical names used: 2-chloro- N -[[(4-methoxy-6-methyl-l,3,5-triazin-2-yl)amino]carbonyl]-benzenesulfonamide (chlorsulfuron); 2-[4-(2,4-dichlorophenoxy)phenoxy]proponoate (diclofop); N -[[(4,6-dimethylpyrimidin-2-yl)amino]carbonyl]-2-methoxycarbonyl-benzenesulfonamide (sulfometuron).

Sign in / Sign up

Export Citation Format

Share Document