Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

Convergence of Probability Measures. By P. Billingsley. Chichester, Sussex, Wiley, 1968. xii, 253 p. 9 1/4“. 117s.

Convergence of Probability Measures

Proceedings of the World Congress on Engineering 2013, WCE 2013

Preface to the Classics Edition Preface Sample course outline 1. Random walk and Brownian motion 2, Discrete-parameter Markov chains 3. Birth-death Markov chains 4. Continuous-parameter Markov chains 5. Brownian motion and diffusions 6. Dynamic programming and stochastic optimization 7. An introduction to stochastic differential equations 8. A probability and measure theory overview Author index Subject index Errata.

http://www.gbv.de/dms/ilmenau/toc/025241613.PDF

Stochastic Processes with Applications

(1) Background: Here, we characterize COVID-19's waves, following a study presenting negative associations between first wave COVID-19 spread parameters and temperature. (2) Methods: Visual examinations of daily increases in confirmed COVID-19 cases in 124 countries, determined first and second waves in 28 countries. (3) Results: The first wave spread rate increases with country mean elevation, median population age, time since wave onset, and decreases with temperature. Spread rates decrease above 1000 m, indicating high ultraviolet lights (UVs) decrease the spread rate. The second wave associations are the opposite, i.e., spread increases with temperature and young age, and decreases with time since wave onset. The earliest second waves started 5-7 April at mutagenic high elevations (Armenia, Algeria). The second waves also occurred at the warm-to-cold season transition (Argentina, Chile). Second vs. first wave spread decreases in most (77%) countries. In countries with late first wave onset, spread rates better fit second than first wave-temperature patterns. In countries with ageing populations (for example, Japan, Sweden, and Ukraine), second waves only adapted to spread at higher temperatures, not to infect the young. (4) Conclusions: First wave viruses evolved towards lower spread. Second wave mutant COVID-19 strain(s) adapted to higher temperature, infecting younger ages and replacing (also in cold conditions) first wave COVID-19 strains. Counterintuitively, low spread strains replace high spread strains, rendering prognostics and extrapolations uncertain.

https://www.mdpi.com/2079-7737/9/8/226/pdf

Inverted Covariate Effects for First versus Mutated Second Wave Covid-19: High Temperature Spread Biased for Young.

Bayesian analysis for detecting a change in exponential family

A new method is
developed to simulate the skew normal distribution. The result is interesting
from a practical as well as a theoretical viewpoint. The new method is simple
to program and is more efficient than the standard method of simulation by
acceptance-rejection method.

A Method to Simulate the Skew Normal Distribution

Nous considerons l'observation des v.a. independantes X 1 ,..., X n qui sont susceptibles de changer de loi apres [nτ 0 ] premieres observations. L'objet est de detecter l'eventuel changement, pour cela nous etudions le comportement de deux tests specifiques de type non-parametrique l'un base sur la comparaison des moyennes avant et apres le changement et l'autre base sur les rangs sequentiels. Sous certaines hypotheses sur l'amplitude de changement, quand le nombre d'observations devient tres grand, la loi des statistiques considerees converge vers celle d'un mouvement Brownien avec drift a partir du temps τ 0 , ce qui permet l'evaluation asymptotique des niveaux et puissances

Étude asymptotique et pratique du comportement de deux tests de détection de rupture

In this paper, for the generating the Skew normal random variables, we propose a new method based on the combination of minimum and maximum of two independent normal random variables. The estimation of parameters using the maximum likelihood estimation and the methods of moments estimation method. A real data set has been considered to illustrate the practical utility of the paper. keyword: Skew normal distribution, maximum likelihood estimation, methods of moments estimation.

https://hal-cnam.archives-ouvertes.fr/hal-02465107/document

Generating the Skew Normal random variable

/pdf/a-method-to-simulate-the-skew-normal-distribution-3yeriggmrl.pdf

Dariush Ghorbanzadeh

Papers

Bayesian analysis for detecting a change in exponential family

A Method to Simulate the Skew Normal Distribution

Étude asymptotique et pratique du comportement de deux tests de détection de rupture

Generating the Skew Normal random variable

A Method to Simulate the Skew Normal Distribution