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The logo consist of "Institut Pertanian Bogor" text, a tree with three branches and five leaves, and an open book which are all lined by a white circle on a blue background. The logo reflects IPB as an academic institution, source of knowledge and technology, with the "Tridarma Perguruan Tinggi" obligation.
The Indonesian Agency for Agricultural Research and Development (Indonesian: Badan Penelitian dan Pengembangan Pertanian, abbreviated as Balitbangtan) abbreviated in English as IAARD was a supporting unit of the Ministry of Agriculture which is responsible for state research, development, and innovation in the field of agriculture in Indonesia.
Curve fitting [1] [2] is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points, [3] possibly subject to constraints. [ 4 ] [ 5 ] Curve fitting can involve either interpolation , [ 6 ] [ 7 ] where an exact fit to the data is required, or smoothing , [ 8 ] [ 9 ] in which a "smooth ...
Inverted logistic S-curve to model the relation between wheat yield and soil salinity. Many natural processes, such as those of complex system learning curves, exhibit a progression from small beginnings that accelerates and approaches a climax over time. When a specific mathematical model is lacking, a sigmoid function is often used.
Crop coefficients are properties of plants used in predicting evapotranspiration (ET). The most basic crop coefficient, K c, is simply the ratio of ET observed for the crop studied over that observed for the well calibrated reference crop under the same conditions.
The best-fit curve is often assumed to be that which minimizes the sum of squared residuals. This is the ordinary least squares (OLS) approach. However, in cases where the dependent variable does not have constant variance, or there are some outliers, a sum of weighted squared residuals may be minimized; see weighted least squares .
Local regression or local polynomial regression, [1] also known as moving regression, [2] is a generalization of the moving average and polynomial regression. [3] Its most common methods, initially developed for scatterplot smoothing, are LOESS (locally estimated scatterplot smoothing) and LOWESS (locally weighted scatterplot smoothing), both pronounced / ˈ l oʊ ɛ s / LOH-ess.