Kernel density estimationIn statistics, kernel density estimation (KDE) is the application of kernel smoothing for probability density estimation, i.e., a non-parametric method to estimate the probability density function of a random variable based on kernels as weights. KDE answers a fundamental data smoothing problem where inferences about the population are made, based on a finite data sample. In some fields such as signal processing and econometrics it is also termed the Parzen–Rosenblatt window method, after Emanuel Parzen and Murray Rosenblatt, who are usually credited with independently creating it in its current form.
Cost estimation in software engineeringCost estimation in software engineering is typically concerned with the financial spend on the effort to develop and test the software, this can also include requirements review, maintenance, training, managing and buying extra equipment, servers and software. Many methods have been developed for estimating software costs for a given project.
Collaborative consumptionCollaborative consumption is the set of those resource circulation systems in which consumers both "obtain" and "provide", temporarily or permanently, valuable resources or services through direct interaction with other consumers or through a mediator. It is sometimes paired with the concept of the "sharing economy". Collaborative consumption is not new; it has always existed (e.g. in the form of flea markets, swap meets, garage sales, car boot sales, and second-hand shops).
