Tag: statistics

Feed: R-bloggers. Author: R on OSM. [This article was first published on R on OSM, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. In our last post, we discussed using the historical average return as one method for setting capital market expectations prior to constructing a satisfactory portfolio. We glossed over setting expectations for future volatility, mainly because it is such a thorny issue. However, we read an excellent tutorial on GARCH models ... Read More

Feed: Planet PostgreSQL. Depending on your workload, the planning time can represent a significant part of the overal query procesing time. This is especially import in OLTP workload, but OLAP queries with numerous tables being joined and an aggressive configuration on the JOIN order search can also lead to hight planning time. Planning counters in pg_stat_statements Previously, pg_stat_statements was only keeping track of the execution part of a query processing: the number of execution, cumulated time, but also minimum, maximum, mean and also the standard deviation. With PostgreSQL 13, you’ll also have those metrics for the planification part! commit 17e03282241c6ac58a714eb0c3b6a8018cf6167a ... Read More

Feed: CronJ. Author: manishkumar; Importance of respiration rate measurement apps:Presently we live in an environment sinking in toxic smoke and polluted air. It is recorded that 2 billion people inhale toxic smoke from burned Bio-mass fuel, 1 billion people inhale polluted outdoor air, and another 1 billion are exposed to tobacco smoke all over the world. This is where the Respiration rate measurement app comes into play by assisting the user to record his BPM (Breath Per Minute) and use the results for improving his health. According to WHO:More than 1 billion people are suffering from either acute or chronic respiratory ... Read More

Feed: AWS Partner Network (APN) Blog. Author: Sanjay Nighojkar. By Suraj Nathani, Sr. Solutions Architect at Mactores CognitionBy Anil Patel, Data Engineer at Mactores CognitionBy Sanjay Nighojkar, Manager, Partner Solutions Architect at AWSSeagate Technology is a United States-based data storage company with worldwide manufacturing facilities that generate huge amounts of manufacturing and testing data. With petabytes of data accumulated over 20 years, and more being generated each day, it was imperative for Seagate to have systems in place to ensure the cost of collecting, storing, and processing data did not exceed their return on investment (ROI). Seagate’s on-premises big data ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Cheryl To. #FlattenTheCurve. #StayHome. #QuarantineLife. They’ve all been trending, and it seems like everybody knows that it’s time to stay at home, indoors, and as far apart (physically) as possible. We’re in the midst of a global pandemic, the worst we’ve seen in a century, yet we still see people out and about, on the streets, congregating in large groups, against the unambiguous advice of experts and health professionals.Why jeopardize public safety? Is it due to a lack of information? A quick online search will produce results on how the virus ... Read More

Feed: R-bloggers. Author: Przemyslaw Biecek. Remote teaching at my university encouraged me to prepare some video materials for Explanatory Model Analysis techniques, i.e. techniques of exploration, explanation and visualisation of predictive models. The pyramid for Explanatory Model Analysis. Left part is focused on a single observation (instance-level or local explanations). Right part is focused on the whole data set (called dataset level or global explanations). In the first row are raw model predictions and model statistics. The second row is related to the analysis of model parts. The third row describes the profile of model behaviour depending on the values ... Read More

Feed: Planet PostgreSQL. Everybody should to know PostgreSQL's stats views: pg_stat_user_tables, pg_stat_database. There are lot of interesting values. For better interpretation we need a difference of these values in some time. It is impossible to get previous value with clean SQL, but in Postgres we can use PLpgSQL, and we can use custom configure variables as session variables. I wrote function buffer, that returns difference between current value and buffered, and save current value to buffer:CREATE OR REPLACE FUNCTION public.buffer_dif(text, bigint) RETURNS bigint LANGUAGE plpgsql AS $function$ DECLARE r bigint; BEGIN r := $2 - current_setting($1, true)::bigint; PERFORM set_config($1, $2::text, ... Read More

Feed: Planet PostgreSQL. On 2nd of April 2020, Fujii Masao committed patch: Allow pg_stat_statements to track planning statistics.   This commit makes pg_stat_statements support new GUC pg_stat_statements.track_planning. If this option is enabled, pg_stat_statements tracks the planning statistics of the statements, e.g., the number of times the statement was planned, the total time spent planning the statement, etc. This feature is useful to check the statements that it takes a long time to plan. Previously since pg_stat_statements tracked only the execution statistics, we could not use that for the purpose.   The planning and execution statistics are stored at the end ... Read More

Feed: SAS Blogs. Author: Grant Brooks. Being a state governor has never been more difficult than right at this moment, because the extreme steps governors are being forced to take in order to protect their citizens’ health are having an equally extreme impact on other critical aspects of our society. In the face of social distancing lockdowns, companies are laying off employees, small businesses are shuttering (perhaps permanently), churches and charities are seeing a precipitous decline in donations, and in some areas crime is rising. Governors and their staffs are acting with unprecedented speed, agility and focus in order to ... Read More

Feed: Planet MySQL; Author: MySQL Performance Blog; While there is no magic bullet for MySQL 5.7 database tuning, there are a few areas that can be focused on upfront that can dramatically improve the performance of your MySQL installation. While much information has been published on this topic over the years, I wanted to break down some of the more critical settings that anyone can implement – with no guesswork required.Depending on the version of MySQL you are running, some of the default values used in this post may differ from your install, but the premise is still largely the ... Read More