Online change detection in exponential families with unknown parameters

International audienceThis paper studies online change detection in exponential families when both the parameters before and after change are unknown. We follow a standard statistical approach to sequential change detection with generalized likelihood ratio test statistics. We interpret these statistics within the framework of information geometry, hence providing a unified view of change detection for many common statistical models and corresponding distance functions. Using results from convex duality, we also derive an efficient scheme to compute the exact statistics sequentially, which allows their use in online settings where they are usually approximated for the sake of tractability. This is applied to real-world datasets of various natures, including onset detection in audio signals

Hybrid algorithms for multiple change-point detection in biological sequences

Array comparative genomic hybridization (aCGH) is one of the techniques that can be used to detect copy number variations in DNA sequences in high resolution. It has been identified that abrupt changes in the human genome play a vital role in the progression and development of many complex diseases. In this study we propose two distinct hybrid algorithms that combine efficient sequential change-point detection procedures (the Shiryaev-Roberts procedure and the cumulative sum control chart (CUSUM) procedure) with the Cross-Entropy method, which is an evolutionary stochastic optimization technique to estimate both the number of change-points and their corresponding locations in aCGH data. The proposed hybrid algorithms are applied to both artificially generated data and real aCGH experimental data to illustrate their usefulness. Our results show that the proposed methodologies are effective in detecting multiple change-points in biological sequences of continuous measurements

Evidências de interação genótipo x ambiente sobre características de crescimento em bovinos de corte Evidences of genotype x environment interaction for growth traits in beef cattle

Objetivou-se, com este trabalho, estudar a interação genótipo x ambiente sobre os pesos à desmama (PD) e aos 12 meses de idade (P12), o ganho de peso diário da desmama aos 12 meses de idade (GDA) e o desempenho com base em um índice (CPG) de componentes principais envolvendo essas três características, em um rebanho da raça Canchim. O ambiente foi considerado a época de nascimento (primeiro e segundo semestres) do animal. Para avaliar a interação genótipo x ambiente, foram utilizadas duas metodologias: 1 - estimativas de parâmetros genéticos pelo método da máxima verossimilhança restrita livre de derivadas (REML), com análise bicaráter (mesma característica nas duas épocas), com o modelo estatístico incluindo os efeitos fixos de sexo, ano e mês de nascimento do animal e idade da vaca ao parto como covariável (linear e quadrático) e os efeitos aleatórios de animal e do resíduo; e 2 - semelhante à metodologia 1, porém, no modelo estatístico, incluiu-se ou não o efeito aleatório não correlacionado de touro-época de nascimento, testando a diferença entre os dois modelos pelo teste de razão de verossimilhança. Pela Metodologia 1, as correlações genéticas obtidas para a mesma característica nas duas épocas de nascimento foram iguais a 0,87; 0,97; 0,91 e 0,88, para PD, P12, GDA e CPG, respectivamente. As estimativas de herdabilidade obtidas foram semelhantes para as duas épocas de nascimento, para todas as características estudadas. Pela metodologia 2, o efeito de touro-época de nascimento foi significativo para todas as características estudadas. Estes resultados evidenciam a existência de interação genótipo x época de nascimento para as características estudadas, sugerindo que as avaliações genéticas e a seleção dos animais desse rebanho devem considerar essa interação.<br>The objective of this study was to evaluate the genotype x environment interaction for body weight at weaning (WW) and 12 months of age (W12), average daily gain from weaning to 12 months of age (ADG), and performance based on a principal components index (PC) involving these three traits, in a Canchim (5/8 Charolais + 3/8 Zebu) herd. The environment was the season (semester) of birth, and two methods were used to evaluate the genotype x environment interaction: Method 1 - genetic parameters estimated by the derivative free maximum likelihood method (REML), using two-trait analyses (the same trait in the two seasons), and a model that included the effects of year and month of birth, sex and age of cow as a covariate (linear and quadratic effects), and the random effect of animal; and Method 2 - same methodology as Method 1, but with two statistical models, with or without the uncorrelated random effect of sire - season of birth, testing the difference between the two models using the likelyhood ratio test. By Method 1, the genetic correlations for the same trait in the two environments (seasons) were equal to 0.87, 0.97, 0.91 and 0.88 for WW, W12, ADG and PC, respectively. The heritability estimates were very similar for both environments, for all traits studied. By Method 2, the sire-season of birth effect was significant for all traits studied. These results show evidence of genotype x season of birth interaction for the traits studied, suggesting that, in this herd, genetic evaluation and selection should take this interaction into account