Comparative analysis of hatchability dynamics (CAHD) of eggs in selected hatcheries in Ibadan metropolis

2020 ◽  
Vol 45 (3) ◽  
Author(s):  
T. O. Dauda ◽  
S. O. Omotoso ◽  
V. A. Ojuade ◽  
V. A. Ojuade ◽  
M. K. Akinwale
Keyword(s):  
Time Series ◽  
Comparative Analysis ◽  
Time Series Analysis ◽  
Information Criteria ◽  
Cyclic Variation ◽  
Summary Statistics ◽  
Akaike Information Criteria ◽  
Egg Hatchability ◽  
Series Analysis ◽  
Time Plot

We carried out this study to evaluate the plausibility of the representativeness of time series analysis results using egg hatchability data from 2 selected hatcheries: Bronco and Foresight hatcheries, Oluyole, Ibadan (both at Latitude 7º 23´ N and Longitude 3º 82´ E). The initial summary statistics of egg variables showed that in Bronco hatchery, the quantity of eggs set peaked (14935.53) in the months of November but lowest (11298.91) in the months of March. However, variance of eggs set in the months of September was highest (41018287) but lowest (1613430) in the months of March. The quantity of fertile eggs ranged between 10216.96 (March) and 13527.58 (November). Total number of chicks produced was highest (11966.15) in the months of November and lowest (9265.86) in the months of March. The time plot of egg set for hatching returned an unconditional cyclic variance and similarly with egg transferred. Although, total eggs hatched into chicks had different time plot pattern but it was also an unconditional cyclic variation. The Jarque-Bera (JB) statistics returned for egg set, egg transferred, total chicks hatched and ratio for Bronco hatchery are 1654.92, 1011.46, 38.721 and 57.855, respectively, while that of foresight hatchery are 25.038, 27.006, 235.897 and 365.734, respectively. The acf(x …x ) of the egg variable presented a wider value than that of acf of (x …x ) for foresight hatchery hence, the acf (x …x ) =(x …x ) could not be said to be strictly stationary. However, the acf of the x …x presented a cyclical and reducing acf like the original acf hence, (x …x ) =(x …x ). The acf of the ratio of egg set to total chicks hatched gave cyclical but reducing trend for both Bronco and Foresight hatcheries. These trends were also maintained for the x …x hence xtk+h …x = x …x . TheARIMAmodel of the ratio of the egg hatchability variables has the least corrected akaike information criteria nd Bayesian Information Criteria hence it could be adjudged the most parsimonious.

Information criteria and harmonic models in time series analysis

1990 ◽  
Vol 35 (3-4) ◽  
pp. 187-207 ◽  
Author(s):  
Dominique Haughton ◽  
Jonathan Haughton ◽  
Alan J. Izenman
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Information Criteria ◽  
Series Analysis

scholarly journals Personal Loan Sales Forecasting Through Time Series Analysis

2021 ◽  
Vol 5 (1) ◽  
pp. 44-51
Author(s):  
Ali İhsan ÖZEROĞLU
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Information Criteria ◽  
Great Likelihood ◽  
Future Expectations ◽  
Loan Sales ◽  
Series Analysis ◽  
Resource Needs ◽  
The Right ◽  
Almost All

Almost all state enterprises and private sector companies try to foresee future expectations. From the viewpoint of economic, productive, and efficient business management, this is highly important. By making rational decisions, all enterprises aim to rich maximum profitability by taking sales, cost, human resource needs, profits into account. For this reason, enterprises have to make reliable and reasonable forecasts to take the right decisions.  Such forecasts might be used in budgeting, cost, and profit analysis. Forecasted scenarios might come true in the future with a great likelihood. The researcher utilizing time series analysis assumes that all findings that come out will be almost the same happened in the past. Analyzing the time series consist of four aims such as defining, modeling forecasting, and controlling. To define a series, it is needed to compute definitional statistics and to draw its graphic. The second purpose of analyzing the time series is to find the appropriate model of the time series. With that work called “Time series and application to sale data”, it is tried to make a suitable guess model by analyzing the data of personal loans of a bank 2004-2010 sale data based on unit. During the stagnation stage of the sequence correlogram and root, analyses are performed. The sequence is analyzed with the help of the Eviews 5,1 program. At the end of the survey, it is seen that natural logarithmic personal loan sale sequences are at their level and in the first gap it is not constant and it is also seen that when the second gap is taken, the constant is obtained. The sequence of which the second gap is taken is shown based on time-way graphs and correlogram. When the constant is provided, the guessed model is formed by taking the second gap. The suitability of the model is observed by the correlogram, Akaike information criteria (AIC), and Schwarz information criteria (SIC) merits.

scholarly journals Comparative Analysis of Non-Linear GNSS Geodetic Time Series Filtering Techniques: El Hierro Volcanic Process (2010–2014)

2021 ◽  
Vol 5 (1) ◽  
pp. 23
Author(s):  
Belén Rosado ◽  
Javier Ramírez-Zelaya ◽  
Paola Barba ◽  
Amós de Gil ◽  
Manuel Berrocoso
Keyword(s):  
Time Series ◽  
Comparative Analysis ◽  
Time Series Analysis ◽  
El Hierro ◽  
Series Analysis ◽  
La Palma ◽  
Non Linear ◽  
Gnss Time Series ◽  
Analyze Time Series ◽  
Filtering Techniques

GNSS geodetic time series analysis allows the study of the geodynamic behavior of a specific terrestrial area. These time series define the temporal evolution of the geocentric or topocentric coordinates obtained from geodetic stations, which are linear or non-linear depending, respectively, on the tectonic or volcanic–tectonic character of a region. Linear series are easily modeled but, for the study of nonlinear series, it is necessary to apply filtering techniques that provide a more detailed analysis of their behavior. In this work, a comparative analysis is carried out between different filtering techniques and non–linear GNSS time series analysis: 1sigma–2sigma filter, outlier filter, wavelet analysis, Kalman filter and CATS analysis (Create and Analyze Time Series). This comparative methodology is applied to the time series that describe the volcanic process of El Hierro island (2010–2014). Among them, the time series of the slope distance variation between FRON (El Hierro island) and LPAL (La Palma island) stations is studied, detecting and analyzing the different phases involved in the process.

scholarly journals Thermal-Induced Errors Prediction and Compensation for a Coordinate Boring Machine Based on Time Series Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Jun Yang ◽  
Dongsheng Zhang ◽  
Bin Feng ◽  
Xuesong Mei ◽  
Zhenbang Hu
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Error Compensation ◽  
Prediction Accuracy ◽  
Thermal Error ◽  
Information Criteria ◽  
Error Modeling ◽  
Cnc Machine Tools ◽  
Machining Accuracy ◽  
Series Analysis

To improve the CNC machine tools precision, a thermal error modeling for the motorized spindle was proposed based on time series analysis, considering the length of cutting tools and thermal declined angles, and the real-time error compensation was implemented. A five-point method was applied to measure radial thermal declinations and axial expansion of the spindle with eddy current sensors, solving the problem that the three-point measurement cannot obtain the radial thermal angle errors. Then the stationarity of the thermal error sequences was determined by the Augmented Dickey-Fuller Test Algorithm, and the autocorrelation/partial autocorrelation function was applied to identify the model pattern. By combining both Yule-Walker equations and information criteria, the order and parameters of the models were solved effectively, which improved the prediction accuracy and generalization ability. The results indicated that the prediction accuracy of the time series model could reach up to 90%. In addition, the axial maximum error decreased from 39.6 μm to 7 μm after error compensation, and the machining accuracy was improved by 89.7%. Moreover, theX/Y-direction accuracy can reach up to 77.4% and 86%, respectively, which demonstrated that the proposed methods of measurement, modeling, and compensation were effective.

scholarly journals The Policy Impact of Social Movements: A Replication Through Qualitative Comparative Analysis

2009 ◽  
Vol 14 (4) ◽  
pp. 467-484 ◽  
Author(s):  
Marco Giugni ◽  
Sakura Yamasaki
Keyword(s):  
Time Series ◽  
Social Movements ◽  
Comparative Analysis ◽  
Time Series Analysis ◽  
Social Movement ◽  
Explanatory Power ◽  
Qualitative Comparative Analysis ◽  
Policy Impact ◽  
Series Analysis ◽  
Social Movement Outcomes

This article reanalyzes the data of a previous study on the policy impact of antinuclear, ecology, and peace movements in three countries with the aim of replicating its findings. Our goal is to see whether using a different analytical technique will yield similar results. The previous study used a regression approach to time-series analysis. Here, we use qualitative comparative analysis (QCA) to analyze the previous study's data. Specifically, we test the two main hypotheses based on the joint-effect model of social movement outcomes: (1) that the policy impact of social movements is conditioned by the presence of powerful allies within the institutional arenas, by the presence of a favorable public opinion, and/or by both factors simultaneously; and (2) that social movements are more likely to have policy impacts when they address issues and policy domains of low saliency. In addition, we compare the policy impact of social movements across countries. Our analysis confirms to a large extent the findings of the earlier time-series analysis, namely, the strong explanatory power of the jointeffect model of social movement outcomes and the varying impact of different movements on public policy.

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