Classroom observation data for District C: Momentary time sampling (Technical Report 5). Project AAIMS, Department of CurriculumOlson, J. & Foegen, A. (2006). Classroom Observation Data for District C: Momentary Time Sampling (Technical Report 5). Project AAIMS, Department of Curriculum an ...
Multivariate Time Series refers to a type of data that consists of multiple variables recorded over time, where each variable can have different sampling frequencies, varying numbers of measurements, and different periodicities. It is commonly used in various fields such as industrial automation, health...
It is the author's general observation that a well-conditioned model will solve well with the default integrator; if the model will only solve with one particular integrator, this may be a clue that something is poorly conditioned within it. In principle the system should not ‘notice’ with...
This example considers trending variables, spurious regression, and methods of accommodation in multiple linear regression models. It is the fourth in a series of examples on time series regression, following the presentation in previous examples....
同时,最近的一些工作证明,高质量的图像可以通过建立感知损失函数(不基于逐像素间的差距,取而代之的是从预训练好的CNN中提取高层次的图像特征来求差)图像通过使损失函数最小化来生成,这个策略被应用到了特征倒置6(Mahendran等),特征可视化7,纹理综合及图像风格化9,10。这些方法能产生很高质量的图片,不过很慢,因为...
Time-resolved observation of thermalization in an isolated quantum system. Phys. Rev. Lett. 117, 170401 (2016). ADS PubMed Google Scholar Brydges, T. et al. Probing entanglement entropy via randomized measurements Preprint at https://arxiv.org/abs/1806.05747 (2018). Hayden, P. & Preskill...
However, the FCI output Zt\(\rightarrow\)Wt (without a circle at the tail) tells us that Zt causes Wt, potentially indirectly, but there cannot be a common driver since such a confounder would induce dependencies that are not consistent with the observation that here Yt−1 is ...
In this section we first introduce a general quantitative description of correlations in the context of the autocorrelation function and with examples from short-range persistent models (Sect.3.1). We then give a formal definition of long-range persistence along with a discussion of stationarity (Se...
(also known asserial correlation) patterns in the residual series by quantifying the relationship of the observation with observations at previous time steps. Autocorrelation is similar to regular correlation but between the values in a series and its past values. It forms the basis for the ...
Since the real-time estimation handles the datasets that are available by the most up-to-date time of observation, one would have to adjust possible underestimation due to the time delay from illness onset to death (Nishiura, 2010c). In the following, we use three different statistical measure...