Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.1007/s42521-020-00021-3 http://scihub22266oqcxt.onion/10.1007/s42521-020-00021-3 C7211562!7211562 !33179008     free     free     free Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\33179008 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Digit+Finance 2020 ; 2 (1-2 ): 159-167 Nephropedia Template TP {{tp|p=33179008 |t=2020. COVID-19 contagion and digital finance |pdf=|usr=}}{{33179008 }} gab.com Text COVID-19 contagion and digital finance JO: Digit Finance http://www.kidney.de/pget.php?&tw=1&pmid=33179008 #FOAvip Digital finance is going to be heavily affected by the COVID-19 outbreak. We present a statistical model which can be employed to understand the contagion dynamics of the COVID-19, so that its impact on finance can possibly be anticipated, and digitally monitored. The model is a Poisson autoregression of the daily new observed cases, and considers both short-term and long-term dependence in the infections counts. Model results are presented for the observed time series of China, the first affected country, but can be easily reproduced for all countries. Twit Text FOAVip COVID-19 contagion and digital finance ????Digit Finance http://www.kidney.de/pget.php?&tw=1&pmid=33179008 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33179008 #FOAvip English Wikipedia <ref>{{Cite pmid|33179008 }}</ref> COVID-19 contagion and digital finance #MMPMID33179008 Agosto A ; Giudici P Digit Finance 2020[]; 2 (1-2 ): 159-167 PMID33179008 show ga Digital finance is going to be heavily affected by the COVID-19 outbreak. We present a statistical model which can be employed to understand the contagion dynamics of the COVID-19, so that its impact on finance can possibly be anticipated, and digitally monitored. The model is a Poisson autoregression of the daily new observed cases, and considers both short-term and long-term dependence in the infections counts. Model results are presented for the observed time series of China, the first affected country, but can be easily reproduced for all countries. äCOVID-19 contagion and digital finance (epmc).pdf DeepDyve Pubget Overpricing