scholarly journals Sarima Modeling of Monthly Temperature in the Northern part of Ghana

2021 ◽  
pp. 37-45
Author(s):  
Emmanuel Ayitey ◽  
Justice Kangah ◽  
Frank B. K. Twenefour
Keyword(s):  
Northern Region ◽  
Temperature Data ◽  
Information Criteria ◽  
Sarima Model ◽  
Monthly Temperature ◽  
Augmented Dickey Fuller ◽  
Best Fitting ◽  
Adf Test ◽  
Fitting Model ◽  
Sarima Models

The Sarima model is used in this study to forecast the monthly temperature in Ghana's northern region. The researchers used temperature data from January 1990 to December 2020. The temperature data was found to be stationary using the Augmented Dickey Fuller (ADF) test. The ACF and PACF plots proposed six SARIMA models: SARIMA (1,0,0) (1,0,0) (12), SARIMA (2,0,0) (1,0,0) (12), SARIMA (1,0,1) (1,0,0) (12), SARIMA (0,0,1) (1,0,0) (12), SARIMA (0,0,1) (0,0,1) (12), SARIMA (0,0,1) (0,0,1) (12). The best model was chosen based on the lowest Akaike Information Criteria (AICs) and Bayesian Information Criteria (BIC) values. The Ljung-Box data, among others, were used to determine the model's quality. All diagnostic tests are passed by the SARIMA (1,0,0) (1,0,0) (12) model. As a result, the SARIMA (1,0,0) (1,0,0) (12) is the best-fitting model for predicting monthly temperatures in Ghana's northern region.

scholarly journals Swiss Franc from the Croatian Perspective

2018 ◽  
Vol 7 (3) ◽  
pp. 41-56
Author(s):  
Mile Bošnjak
Keyword(s):  
Financial Integration ◽  
Information Criteria ◽  
Swiss Franc ◽  
Data Sets ◽  
Daily Data ◽  
Time Period ◽  
Best Fitting ◽  
Standard Information ◽  
Safe Haven Currency ◽  
Fitting Model

Abstract In Croatia and other countries of Central and Eastern Europe, as a consequence of deep financial integration and abolition of capital controls, considerable loans to households indexed to the Swiss franc have emerged. Although all of researchers of the Swiss franc do not agree entirely on whether the Swiss franc is a safe haven currency, its property of continuous appreciation is commonly accepted. There was a continuous appreciation of the Swiss franc over the Croatian kuna. This paper examines the performance of several ARCH-based models for Swiss franc against the Croatian kuna on daily data sets within time period from 1997 to 2010. Evaluating the models through standard information criteria Component ARCH (1,1) is found to be the best-fitting model.

Augmented Dickey-Fuller Test and the Lag Length Selection Problem

2011 ◽  
Vol 130-134 ◽  
pp. 3019-3022 ◽  
Author(s):  
Lu Deng
Keyword(s):  
Information Criteria ◽  
Selection Problem ◽  
Selection Methods ◽  
Leg Length ◽  
Selection Models ◽  
Proper Size ◽  
Augmented Dickey Fuller ◽  
Modified Information Criteria ◽  
Adf Test

Many studies indicated that ADF test is very sensitive to different leg length selection models. Based on Hall, and Ng, Perron’s works, this article simulates a more general ARIMA(0,1,q) process and compares the influence of different selection methods to the size and power of the ADF test. Finally, it is proved that the Modified Information Criteria always shows a more proper size and the General to Special Criteria has more robust ADF test properties.

scholarly journals Time Series Analysis of Road Traffic Accidents in Ghana

2021 ◽  
pp. 12-20
Author(s):  
Frank B. K. Twenefour ◽  
Emmanuel Ayitey ◽  
Justice Kangah ◽  
Lewis Brew
Keyword(s):  
Time Series ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Model Building ◽  
Road Traffic ◽  
Information Criteria ◽  
Augmented Dickey Fuller ◽  
Accident Data ◽  
Adf Test

This study uses Time Series models to predict the annual traffic accidents in Ghana. The traffic accidents data spanning from January 1990 to December 2019 was used. The Box-Jenkins model building strategy was used. The Augmented Dickey Fuller (ADF) test showed that the accident data was stationary. Three ARMA models were suggested based on the ACF and PACF plots of the differenced series, these were ARMA (0,0), ARIMA (1,0), and ARMA (2,0). The model with the smallest corrected Akaike Information Criteria (AICs) and Bayesian Information Criteria (BIC) was chosen as the best model. The Ljung-Box statistics among others were used in assessing the quality of the model. ARMA (1,0) was the best model for the Ghana annual Traffic Accident data. The results showed that, from January to July, it would be difficult to make accurate estimates of the number of road incidents for the years leading up to 2020. This was due to the fact that the white noise process values were statistically independent at various times.

165 Effects of Digestible Lysine Level on Growth Performance and Economics of Grow-finish Pigs

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 58-59
Author(s):  
Larissa L Becker ◽  
Emily E Scholtz ◽  
Joel M DeRouchey ◽  
Mike D Tokach ◽  
Jason C Woodworth ◽  
...  
Keyword(s):  
Phase 1 ◽  
Information Criterion ◽  
Response Curves ◽  
Phase 3 ◽  
Ileal Digestibility ◽  
Distillers Dried Grains ◽  
Feed Cost ◽  
Best Fitting ◽  
Dietary Treatments ◽  
Fitting Model

Abstract A total of 2,124 barrows and gilts (PIC 1050′DNA 600, initially 48.9 kg) were used in a 32-d study to determine the optimal dietary standardized ileal digestibility (SID) Lys level in a commercial setting. Pigs were randomly allotted to 1 of 5 dietary treatments with 24 to 27 pigs/pen and 16 replications/treatment. Similar number of barrows and gilts were placed in each pen. Diets were fed over 3 phases (48.9 to 58.6, 58.6 to 70.9, and 70.9 to 80.8 kg respectively). Dietary treatments were corn-soybean meal-based and contained 10 (phase 1 and 2) or 5% (phase 3) distillers dried grains with solubles. Diets were formulated to 85, 95, 103, 110, or 120% of the current Pig Improvement Company (PIC, Hendersonville, TN) SID Lys gilt recommendations with phase 1 SID Lys levels of 0.90, 1.01, 1.09, 1.17 and 1.27%, phase 2 levels of 0.79, 0.87, 0.94, 1.03, and 1.10%, and phase 3 levels of 0.71, 0.78, 0.85, 0.92, and 0.99%, respectively. Dose response curves were evaluated using linear (LM), quadratic polynomial (QP), broken-line linear (BLL), and broken-line quadratic (BLQ) models. For each response variable, the best-fitting model was selected using the Bayesian information criterion. Overall (d 0 to 32), increasing SID Lys increased (linear, P< 0.001) BW, ADG, G:F, Lys intake/d, and Lys intake/kg of gain. Modeling margin over feed cost (MOFC), BLL and QP estimated the requirement at 105.8% and 113.7% respectively. In summary, while growth increased linearly up to 120% of the PIC current feeding level, the optimal MOFC was 106% to 114% depending on the model used.

Genetic and Environmental Influences of Dietary Indices in a UK Female Twin Cohort

2020 ◽  
Vol 23 (6) ◽  
pp. 330-337
Author(s):  
Olatz Mompeo ◽  
Rachel Gibson ◽  
Paraskevi Christofidou ◽  
Tim D. Spector ◽  
Cristina Menni ◽  
...  
Keyword(s):  
Healthy Eating ◽  
Menopausal Status ◽  
Healthy Eating Index ◽  
Healthy Diet ◽  
Nutritional Epidemiology ◽  
Best Fitting ◽  
Heritability Estimates ◽  
Fitting Model ◽  
Dietary Indices ◽  
Health Parameters

AbstractA healthy diet is associated with the improvement or maintenance of health parameters, and several indices have been proposed to assess diet quality comprehensively. Twin studies have found that some specific foods, nutrients and food patterns have a heritable component; however, the heritability of overall dietary intake has not yet been estimated. Here, we compute heritability estimates of the nine most common dietary indices utilized in nutritional epidemiology. We analyzed 2590 female twins from TwinsUK (653 monozygotic [MZ] and 642 dizygotic [DZ] pairs) who completed a 131-item food frequency questionnaire (FFQ). Heritability estimates were computed using structural equation models (SEM) adjusting for body mass index (BMI), smoking status, Index of Multiple Deprivation (IMD), physical activity, menopausal status, energy and alcohol intake. The AE model was the best-fitting model for most of the analyzed dietary scores (seven out of nine), with heritability estimates ranging from 10.1% (95% CI [.02, .18]) for the Dietary Reference Values (DRV) to 42.7% (95% CI [.36, .49]) for the Alternative Healthy Eating Index (A-HEI). The ACE model was the best-fitting model for the Healthy Diet Indicator (HDI) and Healthy Eating Index 2010 (HEI-2010) with heritability estimates of 5.4% (95% CI [−.17, .28]) and 25.4% (95% CI [.05, .46]), respectively. Here, we find that all analyzed dietary indices have a heritable component, suggesting that there is a genetic predisposition regulating what you eat. Future studies should explore genes underlying dietary indices to further understand the genetic disposition toward diet-related health parameters.

Comparing productive vocabulary measures from the CDI and a systematic diary study

1999 ◽  
Vol 26 (1) ◽  
pp. 177-185 ◽  
Author(s):  
BYRON F. ROBINSON ◽  
CAROLYN B. MERVIS
Keyword(s):  
Growth Curves ◽  
Diary Study ◽  
Expressive Vocabulary ◽  
Early Language ◽  
Vocabulary Size ◽  
Early Language Development ◽  
Closed Class ◽  
Communicative Development ◽  
Best Fitting ◽  
Fitting Model

Expressive vocabulary data gathered during a systematic diary study of one male child's early language development are compared to data that would have resulted from longitudinal administration of the MacArthur Communicative Development Inventories spoken vocabulary checklist (CDI). Comparisons are made for (1) the number of words at monthly intervals (9;10.15 to 2;0.15), (2) proportion of words by lexical class (i.e. noun, predicate, closed class, ‘other’), (3) growth curves. The CDI underestimates the number of words in the diary study, with the underestimation increasing as vocabulary size increases. The proportion of diary study words appearing on the CDI differed as a function of lexical class. Finally, despite the differences in vocabulary size, logistic curves proved to be the best fitting model to characterize vocabulary development as measured by both the diary study and the CDI. Implications for the longitudinal use of the CDI are discussed.

scholarly journals Hemispherical variance anomaly and reionization optical depth

2020 ◽  
Vol 499 (3) ◽  
pp. 3563-3570
Author(s):  
Márcio O’Dwyer ◽  
Craig J Copi ◽  
Johanna M Nagy ◽  
C Barth Netterfield ◽  
John Ruhl ◽  
...  
Keyword(s):  
Optical Depth ◽  
Large Scale ◽  
Cold Dark Matter ◽  
Signal To Noise Ratio ◽  
Cosmological Parameters ◽  
Temperature Data ◽  
Microwave Background ◽  
Parameter Uncertainties ◽  
Polarization Data ◽  
Best Fitting

ABSTRACT Cosmic microwave background (CMB) full-sky temperature data show a hemispherical asymmetry in power nearly aligned with the Ecliptic, with the Northern hemisphere displaying an anomalously low variance, while the Southern hemisphere appears consistent with expectations from the best-fitting theory, Lambda Cold Dark Matter (ΛCDM). The low signal-to-noise ratio in current polarization data prevents a similar comparison. Polarization realizations constrained by temperature data show that in ΛCDM the lack of variance is not expected to be present in polarization data. Therefore, a natural way of testing whether the temperature result is a fluke is to measure the variance of CMB polarization components. In anticipation of future CMB experiments that will allow for high-precision large-scale polarization measurements, we study how the variance of polarization depends on ΛCDM-parameter uncertainties by forecasting polarization maps with Planck’s Markov chain Monte Carlo chains. We show that polarization variance is sensitive to present uncertainties in cosmological parameters, mainly due to current poor constraints on the reionization optical depth τ, which drives variance at low multipoles. We demonstrate how the improvement in the τ measurement seen between Planck’s two latest data releases results in a tighter constraint on polarization variance expectations. Finally, we consider even smaller uncertainties on τ and how more precise measurements of τ can drive the expectation for polarization variance in a hemisphere close to that of the cosmic-variance-limited distribution.

scholarly journals PRICE INTERACTIONS AND CAUSAL RELATIONSHIPS AMONG CORN, EXCHANGE RATE AND ANIMAL PROTEIN SOURCES IN NIGERIA

2021 ◽  
Vol 59 (1) ◽  
Author(s):  
Unekwu Onuche
Keyword(s):  
Exchange Rate ◽  
Granger Causality ◽  
Poultry Meat ◽  
Causality Test ◽  
Vector Autoregressive ◽  
Meat Price ◽  
Augmented Dickey Fuller ◽  
Causality Tests ◽  
Short Run ◽  
Adf Test

Price transmissions between corn, exchange rate, poultry meat, and fish were investigated using the data from OECD-FAO for the years 1990-2019, to establish the existence of long-term relationships between them and identify their directions of causality, in order to elicit investmentaiding facts. The augmented Dickey-Fuller (ADF) test, the Johansen cointegration approach and the Granger causality test were employed. Following the ADF test, all series are I(1), while the cointegration test indicates short-run dynamics between them. The Vector Autoregressive (VAR) system reveals that poultry meat price influences all variables, prices of poultry meat and exchange rate relate positively to their own lags, and exchange rate relates positively to lags of poultry meat prices. A positive relationship was noticed between fish price and lags of poultry meat price, while corn price relates positively with lags of poultry meat price. Granger causality tests indicate unidirectional drives from poultry price to fish price, the exchange rate to fish price and poultry meat price to corn price. Responses from prices of fish, corn and poultry to innovations from exchange rate are negative, while positive responses exist in other scenarios. Exchange rate stabilization will mitigate external risks, especially to the fisheries sector, while corn farmers can increase profits in the short-run by exploring knowledge of poultry meat price movements.

scholarly journals Perbandingan Model GAM dan Gamboost dalam Fitting Dataset Sea Surface Temperature

2018 ◽  
Vol 18 (1) ◽  
pp. 39-50
Author(s):  
Miftahuddin Miftahuddin
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Risk Model ◽  
Generalized Additive Models ◽  
Information Criteria ◽  
Additive Models ◽  
Sea Surface ◽  
Akaike Information Criteria ◽  
Fitting Model

Fitting model GAM (generalized additive models) dan Gamboost (generalized additive models by boosting) untuk dataset SST (sea surface temperature) dimaksudkan sebagai upaya mencapai perbaikan fitting model terhadap data SST. Secara umum, model GAM dapat memvisualisasikan masing-masing kovariat, sedangkan model gamboost dapat memvisualisasikan lebih detail kovariatnya dalam beberapa bentuk, baik secara linier dan nonlinier. Pengukuran performance yang digunakan terhadap model adalah nilai AIC (Akaike Information Criteria) dan CV-risk. Model GAM dengan boosting menunjukkan lebih sesuai dalam struktur model, pemilihan model terbaik dan seleksi variabel pada dataset SST. Fitting model GAM dapat menghasilkan pola dan trend masing-masing kovariat meskipun memiliki beberapa gap, sedangkan pada model gamboost memiliki lebih banyak pilihan simultan dalam bentuk linier, nonlinier dan smooth untuk masing-masing kovariat. Kedua pendekatan fitting memiliki kelebihan yang dapat saling melengkapi dalam memodelkan dataset SST.

scholarly journals Identification-Robust Estimates of the Canadian Natural Rate of Interest

2016 ◽  
Vol 91 (1-2) ◽  
pp. 161-176
Author(s):  
Maral Kichian
Keyword(s):  
Interest Rate ◽  
Robust Methods ◽  
Errors In Variables ◽  
Natural Rate ◽  
Real Rate ◽  
Point Estimates ◽  
Natural Rate Of Interest ◽  
Best Fitting ◽  
Estimate Precision ◽  
Fitting Model

The natural rate of interest is an unobservable entity and its measurement presents some important empirical challenges. In this paper, we use identification-robust methods and central bank real-time staff projections to obtain estimates for the equilibrium real rate from contemporaneous and forward-looking Taylor-type interest rate rules. The methods notably account for the potential presence of endogeneity, under-identification, and errors-in-variables concerns. Our applications are conducted on Canadian data. The results reveal some important identification difficulties associated with some of our models, reinforcing the need to use identification-robust methods to estimate such policy functions. Despite these challenges, we are able to obtain fairly comparable point estimates for the real equilibrium interest rate across our different models, and in the case of the best fitting model, also remarkable estimate precision.

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