Li, W.K. and Hui, Y.Y.: Robust residual cross correlation tests for lagged relations in time series. Journal of Statistical Computations and Simulations. 49(1994), 103-109.Li, W. K. & Hui, Y. V. (1994). Robust residual cross correlation tests for lagged relations in time series. ...
Many econometric models are dynamic, using lagged variables to incorporate feedback over time. By contrast, static time series models represent systems that respond exclusively to current events. Lagged variables come in several types: Distributed Lag (DL) variables are lagged values of observed...
API for manipulating time series on top of Apache Spark: lagged time values, rolling statistics (mean, avg, sum, count, etc), AS OF joins, downsampling, and interpolation - databrickslabs/tempo
Imputation of Missing Values in Time Series with Lagged Correlations Missing values are a common problem in real world data and are particularly prevalent in biomedical time series, where a patient's medical record may be sp... SA Rahman,Y Huang,J Claassen,... - IEEE 被引量: 4发表: 2015...
min_values = df.min() # Create a mask for highlighting minimum values mask = pd.DataFrame("", index=df.index, columns=df.columns) for col in cols_to_convert: mask[col] = df[col].apply( lambda x: "font-weight: bold" if x == min_values[col] else "" ) styled_df_copy = styl...
We consider causal discovery from time series using conditional independence (CI) based network learning algorithms such as the PC algorithm. The PC algorithm is divided into a skeleton phase where adjacencies are determined based on efficiently selected CI tests and subsequent phases where links are...
In many time series applications in the social sciences, lagged dependent variables have no obvious causal interpretation, and researchers omit them. When they are left out, the other coefficients take on sensible values. However, when a... CH Achen 被引量: 824发表: 2000年 Orthogonality conditio...
Estimation of parameters in time-series regression models We consider the estimation of the coefficients in a general linear regression model in which some of the explanatory variables are lagged values of the dependent variable. For discussing optimum properties the concept of best unbiased li... J...
2.2 Estimating the Spatially Lagged y Model In a time series model with a temporally lagged yt-1 on the right-hand side, the presence of the temporal lag yt-1 does not create problems for estimation with OLS, provided there is no serial correlation in the residu- als of the regression ...
delta-MAPS accepts as input, datasets defined on a regular two-dimensional grid with time series specified at each point. Two files have to be locate in the main folder: (1) A .txt file containing a single line specifying the path to the folder data (where the dataset is stored). In ...