Package 'npdsim'

Title: Simulate Demand and Attributes for New Products
Description: Simulate demand and attributes for ready to launch new products during their life cycle, or during their introduction and growth phases. You provide the number of products, attributes, time periods and/or other parameters and 'npdsim' can simulate for you the demand for each product during the considered time periods, and the attributes of each product. The simulation for the demand is based on the idea that each product has a shape and a level, where the level is the cumulative demand over the considered time periods, and the shape is the normalized demand across those time periods.
Authors: Mohammed Hichame BENBITOUR [aut, cre, cph]
Maintainer: Mohammed Hichame BENBITOUR <[email protected]>
License: MIT + file LICENSE
Version: 1.0.0
Built: 2026-05-20 06:05:57 UTC
Source: https://github.com/mohammedhichame/npdsim

Help Index

Simulate the Attributes with the Assumption of Dependent Attributes

Description

Simulate the attributes for each product with the assumption that some of the attributes related to shapes are also related to some of the attributes of levels. We mean by dependence the fact that some attributes of a product are related at the same time to its shape and level.

Usage

attribute_sim_dep(
  product_shapes_and_levels,
  attributes_number,
  shape_attributes_number,
  level_attributes_number
)

Arguments

product_shapes_and_levels

A numeric dateframe of three columns: product_id, assigned_shape and assigned_level
attributes_number

The number of attributes
shape_attributes_number

The number of attributes assigned to shape
level_attributes_number

The number of attributes assigned to level

Value

A numeric dateframe of the following columns: product_id, assigned_shape, assigned_level and attributes (as columns)

Examples

attribute_sim_dep(product_shapes_and_levels=
data.frame(product_id=1:4,assigned_shape=c(1,1,2,2),
assigned_level=c(5,3,3,3)),
attributes_number=15,
shape_attributes_number=7,
level_attributes_number=4)

Simulate the Attributes with the Assumption of Independent Attributes

Description

Simulate the attributes for each product with the assumption that the attributes of shapes are independent of the attributes of levels. We mean by independence the fact that each attribute is related to one of the following: shape, level or nothing.

Usage

attribute_sim_ind(
  product_shapes_and_levels,
  attributes_number,
  shape_attributes_number,
  level_attributes_number
)

Arguments

product_shapes_and_levels

A numeric dateframe of three columns: product_id, assigned_shape and assigned_level
attributes_number

The number of attributes
shape_attributes_number

The number of attributes assigned to shape
level_attributes_number

The number of attributes assigned to level

Value

A numeric dateframe of the following columns: product_id, assigned_shape, assigned_level and attributes (as columns)

Examples

attribute_sim_ind(product_shapes_and_levels=
data.frame(product_id=1:4,assigned_shape=c(1,1,2,2),
assigned_level=c(5,3,3,3)),
attributes_number=15,
shape_attributes_number=7,
level_attributes_number=4)

Simulate the demand for new products

Description

Simulate the demand for new products over their life cycle by specifying their shape type.

Usage

demand_sim(
  products_number,
  periods_number,
  shape_number,
  shape_type = "random",
  level_number,
  level_range = 1000:10000,
  noise_cv = 0.05
)

Arguments

products_number

Number of products
periods_number

Number of periods of the introduction and growth phases
shape_number

Number of generic shapes
shape_type

Type of shape to generate. It can take the values: "triangle", "trapezoid", "bass", "random" and "intro & growth". The type "random" picks one of the types "triangle", "trapezoid", "bass" randomly for each product. The type "intro & growth" is used for the shapes of the introduction and growth phases.
level_number

Number of generic levels
level_range

Range of values from which the level is sampled
noise_cv

The coefficient of variation of the noise added to the simulated sales

Value

A date frame that contains the following columns: product_id, shape and assigned_shape, level and assigned_level, demand_wn (demand without noise, not rounded), noise and demand. demand is the rounded value of the Max between (demand_wn+noise) and 0

Examples

demand_sim(products_number=100,periods_number=20,shape_number=5, level_number=20)

demand_sim(products_number=100,periods_number=20,shape_number=5, shape_type="bass", level_number=20,
level_range=1000:10000,noise_cv=0.05)

Simulate the demand and attributes for new products

Description

Simulate the demand and attributes for new products during their life cycle by specifying their life cycle type of shape and providing information about their attributes.

Usage

npd_data_sim(
  products_number,
  periods_number,
  shape_number,
  shape_type = "random",
  level_number,
  level_range = 1000:10000,
  noise_cv = 0.05,
  attribute_type = "ind",
  attributes_number = 10,
  shape_attributes_number = 5,
  level_attributes_number = 3
)

Arguments

products_number

Number of products
periods_number

Number of periods of the introduction and growth phases
shape_number

Number of generic shapes
shape_type

Type of shape to generate. It can take the values: "triangle", "trapezoid", "bass", "random" and "intro & growth". The type "random" picks one of the types "triangle", "trapezoid", "bass" randomly for each product. The type "intro & growth" is used for the shapes of the introduction and growth phases.
level_number

Number of generic levels
level_range

Range of values from which the level is sampled
noise_cv

The coefficient of variation of the noise added to the simulated sales
attribute_type

Type of relationship between attributes and shape and level. There can be independent attributes or dependent attributes. attribute_type takes one of the two values: "dep" and "ind". Check 'attribute_sim_dep' and 'attribute_sim_dep'.
attributes_number

The number of attributes
shape_attributes_number

The number of attributes assigned to shape
level_attributes_number

The number of attributes assigned to level

Value

A date frame that contains the following columns: product_id, demand and attributes.

Examples

npd_data_sim(products_number=100,
periods_number=30,
shape_number=5,
level_number=20)

npd_data_sim(products_number=100,
periods_number=20,
shape_number=5,
shape_type="bass",
level_number=20,
level_range=1000:10000,
noise_cv=0.05,
attribute_type="ind",
attributes_number=15,
shape_attributes_number=7,
level_attributes_number=5)

Calculate the Bass probability

Description

Calculate the Bass probability density function of purchase f(t)

Usage

npdsim_bass(p_param, q_param, t)

Arguments

p_param

Coefficient of innovation
q_param

Coefficient of imitation
t

A numeric vector of time periods

Value

A numeric vector of the probability density function of purchase at time t, f(t)

Examples

npdsim_bass(p_param=0.01,q_param=0.2, t=1:20)

Generate the shape of demand

Description

Generate the shape of demand for new products by specifying their life cycle shape and the length of their life cycle

Usage

shape_sim(periods_number, shape_number, shape_type = "random")

Arguments

periods_number

Number of time periods of the products life cycle
shape_number

Number of generic shapes
shape_type

Type of shape to generate. It can take the values: "triangle", "trapezoid", "bass", "random" and "intro & growth". The type "random" picks one of the types "triangle", "trapezoid", "bass" randomly for each product. The type "intro & growth" is used for the shapes of the introduction and growth phases.

Value

A numeric dateframe of three columns: time, shape and assigned_shape

Examples

shape_sim(periods_number=20, shape_number=5)
shape_sim(periods_number=20, shape_number=5,shape_type="trapezoid")

Generate generic Bass shapes

Description

Generate generic Bass shapes for the demand of new products during their life cycle

Usage

shape_sim_bass(periods_number, shape_number)

Arguments

periods_number

Number of time periods of the products life cycle
shape_number

Number of generic shapes

Value

A numeric dateframe of three columns: time, shape and assigned_shape

Examples

shape_sim_bass(periods_number=20, shape_number=5)

Generate generic shapes for the introduction and growth phases

Description

Generate piece-wise linear (4 segments) generic shapes for the introduction and growth phases

Usage

shape_sim_ig(periods_number, shape_number)

Arguments

periods_number

Number of periods of the introduction and growth phases
shape_number

Number of generic shapes

Value

A numeric dateframe of three columns: time, shape and assigned_shape

Examples

shape_sim_ig(periods_number=20, shape_number=5)

Generate random (Bass, Trapezoidal or Triangular) shapes

Description

Generate random (Bass, Trapezoidal or Triangular) shapes for the demand of new products during their life cycle

Usage

shape_sim_random(periods_number, shape_number)

Arguments

periods_number

Number of time periods of the products life cycle
shape_number

Number of generic shapes

Value

A numeric dateframe of three columns: time, shape and assigned_shape

Examples

shape_sim_random(periods_number=20, shape_number=5)

Generate trapezoidal shapes

Description

Generate trapezoidal shapes for the demand of new products during their life cycle

Usage

shape_sim_trapezoid(periods_number, shape_number)

Arguments

periods_number

Number of time periods of the products life cycle
shape_number

Number of generic shapes

Value

A numeric dateframe of three columns: time, shape and assigned_shape

Examples

shape_sim_trapezoid(periods_number=20, shape_number=5)

Generate triangular shapes

Description

Generate triangular shapes for the demand of new products during their life cycle

Usage

shape_sim_triangle(periods_number, shape_number)

Arguments

periods_number

Number of time periods of the products life cycle
shape_number

Number of generic shapes

Value

A numeric dateframe of three columns: time, shape and assigned_shape

Examples

shape_sim_triangle(periods_number=20, shape_number=5)