搜索资源列表
Linear-regression-analysis
- 对采集的样例数据进行回归分析,包括一元、多元和病态回归三种情况,并在一定执行概率给出置信区间和回归预测-The collected sample data, regression analysis, including a dollar return of three cases and pathological diversity, and given a certain probability of confidence intervals and perform regression
1
- 线性回归,最小二乘法参数估计,0.95的置信区间的估计,预测-Linear regression
vol
- matlab金融时间序列ARMA建模 结果分析: 1.预测结果从第四步开始,预测值不再改变,因为ARMA是收敛的回归模型,而我们做的工作并不是模拟,所以,当预测步长足够长时,它最终将收敛于一个不变得预测值 2.既然预测值一样,为什么还原为成交量后,在置信区间下预测的最大值与预测均值的差比预测均值与最小值的差要大?因为将对数差分值还原时,需用到的指数函数为凹函数-matlab Financial Time Series the the ARMA modeling results Ana
AR_with_remove
- 时间序列分析,AR模型,用于流数据预测与滤波 输入参数:y为原始数据矩阵,p为AR模型的阶数,la为自回归模型的遗忘系数 输出参数:预测值,置信区间,离群点等-Time series analysis, AR model for prediction and filtering data stream input parameters: y original data matrix, p is the order of the AR model, la self-forgetting c
svm-confidence-interval
- lssvm 最小二乘支持向量机回归模型置信区间预测, 简单易用,易懂易学-least squares support vector machine
锂电池退化GPR
- 高斯过程回归是一种基于贝叶斯原理的统计机器学习方法,将先验分布通过贝叶斯定理转化成后验分布,与其他没有采用贝叶斯技巧的预测方法而言,高斯过程最大的优点是能方便地推断出超参数,同时也能方便地给出预测值的置信区间(Gaussian Process Regression is a statistical machine learning method based on Bayesian principle. It transforms prior distribution into posterio
线性回归预测置信区间
- 一组数据的线性回归预测,并给出了预测的置信区间!!!(prediction of linear regression, and Confidence Interval)
DBN
- 根据历史电网负荷数据,用深度置信网络预测未来负荷大小(Forecast future load size based on historical grid load data)
DBN
- 基于Tensorflow的典型深度学习模型-深度置信网络预测程序,方便拓展,测试文件在test文件夹下(The typical deep learning model based on tensorflow deep confidence network prediction program is easy to expand, with case data attached, and the test file is in the test folder)