A class of dynamic piecewise exponential models with random time grid

2012 ◽  
Vol 142 (3) ◽  
pp. 728-742 ◽  
Author(s):  
Fabio N. Demarqui ◽  
Rosangela H. Loschi ◽  
Dipak K. Dey ◽  
Enrico A. Colosimo
2011 ◽  
pp. 109-122
Author(s):  
Fabio N. Demarqui ◽  
Dipak K. Dey ◽  
Rosangela H. Loschi ◽  
Enrico A. Colosimo

2017 ◽  
Vol 9 (12) ◽  
pp. 43
Author(s):  
Ryosuke Iida ◽  
Carlos Piñeiro ◽  
Yuzo Koketsu

Our objective was to characterize eating behavior associated with displacement hazard and subsequent performance for pigs were fed in static groups by an electronic sow feeder (ESF). Data included weekly eating records and subsequent farrowing records of 685 pigs. The eating behavior comprised weekly averages of daily feed dispensed (ADFD) and daily total time spent in the feeding stations (TTSF). A displacement female was defined as a pig removed from her group for health reasons. A multivariate model and piecewise exponential models were fitted to the records. Means (inter-quartile ranges) of ADFD and TTSF were 2.4 kg (2.1-2.8 kg) and 9.3 min (7.5-10.8 min), respectively. Gilts had less ADFD than sows during gestational weeks 5-13 (P < 0.05), but there was no difference in TTSF between gilts and sows in gestational weeks 5-8 and 11-13 (P > 0.05). Also, gilts had higher displacement hazard than parity 2 or higher sows in gestational weeks 8-10 (P < 0.05). Pigs that were entered into the ESF system during summer had less ADFD, and shorter TTSF from gestational weeks 5 to 12 than those entered during the other seasons (P < 0.05). The TTSF varied between two genotypes during gestational weeks 5-7 (P < 0.05). Also, a higher displacement hazard was associated with less ADFD (P < 0.01). A higher hazard of pregnancy loss was associated with shorter TTSF (P < 0.01). In conclusion, we recommend that both ADFD and TTSF should be measured in ESF systems to help identity females having problems.


2013 ◽  
Vol 13 (1) ◽  
Author(s):  
Jessica Kubo ◽  
Mark R Cullen ◽  
Linda Cantley ◽  
Martin Slade ◽  
Baylah Tessier-Sherman ◽  
...  

Stat ◽  
2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Andrew Wey ◽  
Nicholas Salkowski ◽  
Walter Kremers ◽  
Yoon Son Ahn ◽  
Jon Snyder

2020 ◽  
Vol 4 (1) ◽  
pp. 1
Author(s):  
Christian Ebere Enyoh ◽  
Andrew Wirnkor Verla ◽  
Chidi Edbert Duru ◽  
Emmanuel Chinedu Enyoh ◽  
Budi Setiawan

Based on the official Nigeria Centre for Disease Control (NCDC) data, the current research paper modeled the confirmed cases of the novel coronavirus disease 2019 (COVID-19) in Nigeria. Ten different curve regression models including linear, logarithmic, inverse, quadratic, cubic, compound, power, S-curve, growth, and exponential were used to fit the obtained official data. The cubic (R2 = 0.999) model gave the best fit for the entire country. However, the growth and exponential had the lowest standard error of estimate (0.958) and thus may best be used. The equations for these models were e0.78897+0.0944x and 2.2011e0.0944x respectively. In terms of confirmed cases in individual State, quadratic, cubic, compound, growth, power and exponential models generally best describe the official data for many states except for the state of Kogi which is best fitted with S-curve and inverse models.  The error between the model and the official data curve is quite small especially for compound, power, growth and exponential models. The computed models will help to realized forward prediction and backward inference of the epidemic situation in Nigeria, and the relevant analysis help Federal and State governments to make vital decisions on how to manage the lockdown in the country.


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