The first edition of this book (1970) set out a systematic basis for the analysis of binary data and in particular for the study of how the probability of 'success' depends on explanatory variables. The first e
Journal of the Royal Statistical Society Series A: Statistics in SocietyCox, D.R., 1970. The Analysis of Binary Data. Chapman and Hall, New York, NY.Cox, D.R. (1970). The Analysis of Binary Data. London: Chapman and Hall.Cox D. R., and Snell E. J. The analysis of binary data...
Analysis of Binary Data (2nd ed.).by D. R. Cox; E. J. Snell RBD Steffey - 《Journal of the American Statistical Association》 被引量: 0发表: 1990年 Data Analysis for Database Design - Pages 317-318 - ScienceDirect Data Analysis for Data Base Design, 2nd Ed - Howe - 1989 () ...
Statistics for quantifying heterogeneity in univariate and bivariate meta-analyses of binary data: the case of meta-analyses of diagnostic accuracy. Stat Med. 2014;33(16):2701–17. Article PubMed Google Scholar Borchers HW. pracma: Practical Numerical Math Functions 2021 [2.3.3:[Available from:...
Statistical visualizations let you find the important bits in a sea of binary data - all at a glance. See our home page at https://veles.io or visit us on IRC: #veles at freenode. Binaries You can download compiled binaries at https://veles.io or https://github.com/codilime/veles/...
Binary installers for the latest released version are available at thePython Package Index (PyPI)and onConda. #condaconda install -c conda-forge pandas #or PyPIpip install pandas The list of changes to pandas between each release can be foundhere. For full details, see the commit logs athttp...
IDA, the ultimate binary analysis solution for reverse engineering, malware analysis, and vulnerability reporting.
While importing analysis data, bnida computes offsets for analysis objects relative to section start addresses. This ensures imports are accurate even if the binary has been rebased. In the case of raw binaries that are loaded via Binary Ninja's mapped view, sections must be applied manually....
The former converts the original multi-labeled data into a set of binary or multi-class data sets, whereas for the latter, the multi-label support is embedded into the algorithm’s structure. Thus, the transformation approach fits the data to the algorithms, and the adaptation approach fits ...
Distributed health data networks (DHDNs) leverage data from multiple sources or sites such as electronic health records (EHRs) from multiple healthcare systems and have drawn increasing interests in recent years, as they do not require sharing of subject