例如,你可以使用autocorrelation函数计算自相关系数,使用fft函数进行快速傅里叶变换,以及使用wavelet函数进行小波变换。 HyperTS支持多种常见的时间序列模型,如ARIMA、GARCH、VAR等。这些模型可以用于时间序列的建模和预测。例如,你可以使用arima函数建立ARIMA模型,使用garch函数建立GARCH模型,以及使用var函数建立VAR模型。 Hyper...
bayesGARCH 2.1.10 bayesm 3.1-6 bayesmix 0.7-6 bayesplot 1.11.1 bayesQR 2.4 bayesSurv 3.7 bayestestR 0.14.0 BayesTree 0.3-1.5 BayesX 0.3-3 BCBCSF 1.0-1 BDgraph 2.73 beanplot 1.3.1 beepr 2 beeswarm 0.4.0 benford.analysis 0.1.5 BenfordTests 1.2.0 bfp 0.0-48 BH 1.84.0-0 bi...
Understand the ARCH and GARCH processes and how to write related Python programs In Detail This book uses Python as its computational tool. Since Python is free, any school or organization can download and use it. This book is organized according to various finance subjects. In other words, th...
python主题建模可视化LDA和T-SNE交互式可视化|附代码数据 我尝试使用Latent Dirichlet分配LDA来提取一些主题。 本教程以自然语言处理流程为特色,从原始数据开始,准备,建模,可视化论文。 我们将涉及以下几点 使用LDA进行主题建模 使用pyLDAvis可视化主题模型 使用t-SNE可视化LDA结果 In [1]: from scipy import sparse as ...
are parameters to be estimated and p and q are maximum lag in the model. To have consistent GARCH the following conditions should hold: ω > 0 β ≥ 0 α 0 β+ α < 1 The ARCHmodel is unableto capture the influence of historical innovations. However, as a more ...
Chapter 4, Multi-Factor Models, shows how to estimate various factor models in Python. I start with the simplest one-factor model and then explain how to estimate more advanced three-, four-, and five-factor models. Chapter 5, Modeling Volatility with GARCH Class Models, introduces the reader...
Result[Result.multi_class==6]['rnn_pred'].hist() <matplotlib.axes._subplots.AxesSubplot at 0x7f86a1938128> Res.plot(figsize=(20,10)) g.map(sns.distplot, "return",); 结论 本文提出了一种基于注意力机制的RNN模型用于股票价格预测,并通过实验验证了其有效性。与基线模型相比,该模型在预测性能上取...
params: array, (nobs, 2) array of mean, variance (mu, sigma2) with observations in rows df : integer degrees of freedom of the t distribution Returns --- lls : array contribution to loglikelihood for each observation Notes --- parameterized for garch ''' mu, sigma2 = params.T df =...
bayesGARCH 2.1.10 bayesm 3.1-6 bayesmix 0.7-6 bayesplot 1.11.1 bayesQR 2.4 bayesSurv 3.7 bayestestR 0.14.0 BayesTree 0.3-1.5 BayesX 0.3-3 BCBCSF 1.0-1 BDgraph 2.73 beanplot 1.3.1 beepr 2 beeswarm 0.4.0 benford.analysis 0.1.5 BenfordTests 1.2.0 bfp 0.0-48 BH 1.84.0-0 b...
1 相关研究综述在时间序列异常检测的研究中,对于检测对象而言,可分为点异常、子序列异常、模式异常这 3 类研究任务.对于异常检测方法而言,主要有基于统计模型(如 ARIMA,GARCH 等)、基于聚类(如 k-means,EM,SVM 模型等)、 基于相似性度量、基于约束规则等.2 研究问题介绍2.1 基本定义 本文提出的方法对所有维度时...