Analysing Cycles in Biology and Medicine: A Practical Introduction to Circular Variables and Periodic Regression. Second Edition. By K. N. I. Bell. St. John's (Canada): Razorbill Press. $25.95 (paper). xv + 163 p.; ill.; index. ISBN: 978‐0‐9736209‐2‐4. 2008.

2010 ◽  
Vol 85 (1) ◽  
pp. 123-123
Author(s):  
F. James Rohlf
Keyword(s):  
Periodic Regression

Seasonal variations in serum lipid and apolipoprotein levels evaluated by periodic regression analyses

1982 ◽  
Vol 35 (8) ◽  
pp. 643-648 ◽  
Author(s):  
Gunnar Fager ◽  
Olle Wiklund ◽  
Sven-Olof Olofsson ◽  
Göran Bondjers
Keyword(s):  
Seasonal Variations ◽  
Serum Lipid ◽  
Regression Analyses ◽  
Periodic Regression

SEMI-PARAMETRIC AND NON-PARAMETRIC MODELING OF THE TEMPORAL ACTIVITY OF THE HYPOTHALAMIC PULSE GENERATOR IN CASTRATE MONKEYS

1995 ◽  
Vol 03 (04) ◽  
pp. 1125-1129
Author(s):  
A.-C. CAMPROUX ◽  
J.-P. JAIS ◽  
J.-C. THALABARD ◽  
G. THOMAS
Keyword(s):  
Experimental Data ◽  
Process Model ◽  
Pulse Generator ◽  
Temporal Structure ◽  
Parametric Modeling ◽  
Parametric Approach ◽  
Stochastic Point Process ◽  
Periodic Regression ◽  
Ovariectomized Rhesus Monkey ◽  
Non Parametric

The luteinizing hormone (LH) is released by the pituitary in discrete pulses. Electro-physiological studies in monkeys have demonstrated that sharp intermittent increases in the electrical activity of a hypothalamic pulse generator (HPG) are associated in a one-to-one manner with the occurrence of LH pulses in the plasma and exhibits a circadian modulation. In order to investigate the temporal structure of the HPG, we develop a semi-parametric stochastic point process model generalizing the Cox's periodic regression model. We apply this approach to the study of memory range of the process underlying HPG activity, using experimental data from one ovariectomized rhesus monkey. A non-parametric approach is also described.

Periodic regression in long-term agricultural experiments

1980 ◽  
Vol 95 (1) ◽  
pp. 233-234 ◽  
Author(s):  
E. A. Roberts
Keyword(s):  
Seasonal Pattern ◽  
Periodic Regression

Evans & Roberts (1979) considered that loworder polynomials such as mean, linear and quadratic were adequate to describe the trends that occur in treatment contrasts in long-term agricultural experiments. This conclusion was based on experience with experiments on levels of fertilizers and rates of stocking on similar pastures. In such experiments, the marked seasonal pattern in the data disappears when comparisons between treatments are followed. However, further experience with experiments comparing cultivars has shown that some comparisons still show a seasonal pattern. Such patterns may be accounted for by periodic regression (Bliss, 1970).

scholarly journals The Developmental Acquisition of Motion

1986 ◽  
Vol 1 (2) ◽  
pp. 67-75
Author(s):  
Samuel Juni ◽  
Scott Budge
Keyword(s):  
Philosophical Inquiry ◽  
The Past ◽  
Time Space ◽  
The World ◽  
Space Motion ◽  
Governing Principle ◽  
Periodic Regression ◽  
Integration Algorithms ◽  
Historical Antecedents ◽  
Generalized Expectancies

Under the general rubric of the development of object constancy and permanence, the concepts of time, space, motion, and noncentrist motion are assimilated through a hierarchy of steps. This developmental continuum begins at the pervasive ego-centric position of early infancy, where there is no concept of the outside world, and ends at the stage where the world serves as the frame of reference for all subjectively perceived events. The general impetus for movement along this continuum (with allowance for periodic regression) is formulated as a basic tendency to generalize from unitary experience into generalized expectancies. This tendency manifests through integration algorithms that are expressed by establishing induction as a governing principle of phenomenological expectancies, thus forming the essence of a systematic explanatory network comprising an internalized catalog of events the person had encountered in the past. Such historical antecedents serve to extract certain contingencies from the heretofore unexplained or "magical" domain of childhood logic and enable their codification as explainable events. We suggest that this is precisely the opposite of a parallel process that proceeds from total noncentricity to phenomenology of subjectivity: philosophical inquiry into logic events.

scholarly journals Future trends of COVID-19 disease outbreak in different states in India: a periodic regression analysis

2020 ◽  
Author(s):  
Bharath Prasad Cholanayakanahalli Thyagaraju ◽  
Srikantha Gowda ◽  
Sharanagouda Patil ◽  
Chandrashekar Srikantiah ◽  
Kuralayanapalya Puttahonnappa Suresh
Keyword(s):  
Tamil Nadu ◽  
Time Series Data ◽  
Human Life ◽  
Disease Outbreak ◽  
Series Data ◽  
Indian Government ◽  
Economic Wealth ◽  
The Future ◽  
Periodic Regression ◽  
The Impact

COVID-19 (Coronavirus disease 19) is the deadliest pandemic, and by August 2, >18.2 million population worldwide were infected with SARS-CoV-2 virus causing burden on human life and economic loss. Disease outbreak analysis has become a priority for the Indian government to initiate necessary healthcare measures in lowering the impact of this deadly pandemic viral disease. In this study, time series data for COVID-19 disease was extracted from the website www.covid19india.org, analysed by using periodic regression model, the expected number of cases till 02 October 2020 was predicted and to develop a stochastic models using periodic regression in the top 15 highly infected states in India. The analysis reported increasing pattern at initial days of prediction and showed a decreasing trend for the number of reporting cases, which may reduce in future days for states like West Bengal, Karnataka, Uttar Pradesh, Bihar, Telangana, Assam and Odisha. However, for the states of Maharashtra, Tamil Nadu, Gujarat, Rajasthan, Haryana and Madhya Pradesh, showed a rapid phase of increase in disease outbreak that is likely to infect more population and indicates the pandemic nature of this disease over a period. Presently, Delhi shows a drastic reduction in the number of cases, that may increase in the future, which can be controlled if appropriate preventive measures are followed strictly and effectively. Our model highlights that continuous and constant efforts are needed for the prevention of new infections of the disease in all states that helps to effectively mitigate the disease and to allocate scarce resources effectively in the future that could improve the economic wealth in India.

PSII-2 Daily patterns for respiration rates and internal temperatures of heat stressed lactating sows with or without electronically controlled cooling pads

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 321-321
Author(s):  
Jason R Graham ◽  
Michaiah J Galvin ◽  
Taylor L Jansen ◽  
Tyler C Field ◽  
Robert M Stwalley ◽  
...  
Keyword(s):  
Single Phase ◽  
Mixed Model ◽  
Random Effect ◽  
Regression Equations ◽  
Controlled Cooling ◽  
Study Objective ◽  
Final Model ◽  
Lactating Sows ◽  
Periodic Regression ◽  
The Impact

Abstract Lactating sows are especially sensitive to heat stress (HS) due to high metabolic demands resulting from milk output. Therefore, there is a need to develop effective cooling technologies that reduce the impact of HS on lactating sows. The study objective was to determine whether electronically controlled cooling pads (ECP) would allow sows to remain euthermic under HS conditions. Twelve multiparous (2.69 ± 0.85) lactating sows (265.4 ± 26.1 kg) and litters (11.4 ± 0.7 piglets/litter) were assigned to either a non-functional ECP (NECP; n = 6) or an ECP (n = 6), housed in farrowing crates, and tested over two repetitions. Sows were provided feed and water ad libitum and all sows were exposed to HS (28.27 ± 1.42°C nighttime to 35.14 ± 0.70°C daytime). Body temperature (TB), was measured hourly using vaginal implants, and respiration rate (RR) was measured in 30 min intervals from 0600 to 2100 hrs over 2 d representing mid- and late lactation. Mixed model periodic regression equations were fitted to the TB and RR to time. The final model for TB included the effect of replicate, random effect of sow, day of lactation as a covariate, single-phase sine and cosine variables for each treatment and 2-phase sine and cosine periodic regression variables. The final model for RR included the random effect of sow, effect of treatment, replicate, day of lactation, sleeping, and single-phase sine and cosine functions for each treatment. An interaction (P < 0.05) between treatment and sine or cosine was observed for TB. For RR there was no interaction for treatment and cosine (P = 0.07), but an interaction (P < 0.05; -9.94) was observed for sine. The significant treatment by wavelength interactions observed indicate a change in RR and TB patterns when sows are placed on ECPs.

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